{"as_of":"2026-08-09T00:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:99ec85a7dd2debf6b26995517f36be58ec4f88b7d0890060c1d687ee7318cbb0","coverage":[{"denominator":61,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":61,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:42:15.886444Z","state":"measured"},{"denominator":65,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":65,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-01T00:19:41.616050Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T00:09:14.755456Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"cited_work":{"arxiv_id":"2506.07310","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.07310","snapshot_observed_at":"2026-07-04T00:09:14.755456Z","title":"Alltracker: Efficient dense point tracking at high resolution","venue":null,"work_id":"2e295123-23bf-413a-ac13-c5957d6e8531","year":2025},"citing_paper":{"arxiv_id":"2605.02849","last_updated":"2026-06-09T21:58:58Z","snapshot_observed_at":"2026-07-06T23:15:51.008483Z","submitted_at":"2026-05-04T17:25:14Z","title":"Active Sampling for Ultra-Low-Bit-Rate Video Compression via Conditional Controlled Diffusion","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-05-08T18:29:57.042720Z"},"links":{"cited_paper":"/paper/2506.07310","citing_paper":"/paper/2605.02849"},"observation_digest":"sha256:3284e7abdd2772e67d3554d94642945ebe92ccb3a21a27af4e1e96f11f7a587f","observation_id":"ce7b576e-95e1-4f5f-9e84-12651e2e8ce8","resolution":{"observed_at":"2026-05-09T06:25:40.446045Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"cited_work":{"arxiv_id":"2506.07310","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.07310","snapshot_observed_at":"2026-07-04T00:09:14.755456Z","title":"Alltracker: Efficient dense point tracking at high resolution","venue":null,"work_id":"2e295123-23bf-413a-ac13-c5957d6e8531","year":2025},"citing_paper":{"arxiv_id":"2605.02849","last_updated":"2026-06-09T21:58:58Z","snapshot_observed_at":"2026-07-06T23:15:51.008483Z","submitted_at":"2026-05-04T17:25:14Z","title":"Active Sampling for Ultra-Low-Bit-Rate Video Compression via Conditional Controlled Diffusion","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-01T00:19:41.616050Z"},"links":{"cited_paper":"/paper/2506.07310","citing_paper":"/paper/2605.02849"},"observation_digest":"sha256:41a9b7ae6c02561c2dc60e770033535412f78d9231a39e43b1b42554b96ee6c1","observation_id":"1afc062e-4028-4f4f-89db-4b9788bf39bd","resolution":{"observed_at":"2026-07-01T00:25:09.660534Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"cited_work":{"arxiv_id":"2506.07310","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.07310","snapshot_observed_at":"2026-07-04T00:09:14.755456Z","title":"Alltracker: Efficient dense point tracking at high resolution","venue":null,"work_id":"2e295123-23bf-413a-ac13-c5957d6e8531","year":2025},"citing_paper":{"arxiv_id":"2605.18052","last_updated":"2026-05-18T08:41:10Z","snapshot_observed_at":"2026-07-06T23:28:59.503300Z","submitted_at":"2026-05-18T08:41:10Z","title":"Efficient 3D Content Reconstruction and Generation","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-20T11:38:48.194538Z"},"links":{"cited_paper":"/paper/2506.07310","citing_paper":"/paper/2605.18052"},"observation_digest":"sha256:e8b1c54778296fa1860d8c3773dae327d22da2576bc9d43a71f77ee16e720b0e","observation_id":"d1ad93aa-5e3d-407d-b47e-287745d3d1e1","resolution":{"observed_at":"2026-05-20T11:43:15.382028Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"cited_work":{"arxiv_id":"2506.07310","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.07310","snapshot_observed_at":"2026-07-04T00:09:14.755456Z","title":"Alltracker: Efficient dense point tracking at high resolution","venue":null,"work_id":"2e295123-23bf-413a-ac13-c5957d6e8531","year":2025},"citing_paper":{"arxiv_id":"2606.18558","last_updated":"2026-06-17T00:19:00Z","snapshot_observed_at":"2026-07-06T23:53:59.519305Z","submitted_at":"2026-06-17T00:19:00Z","title":"MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-26T21:27:47.702578Z"},"links":{"cited_paper":"/paper/2506.07310","citing_paper":"/paper/2606.18558"},"observation_digest":"sha256:2f48569ce11f9892a990f38438c4fbf10f0a34b43f7ccba2a7c0e7328d2eabf3","observation_id":"03d5f688-914f-4dac-adae-e16ce98d67b5","resolution":{"observed_at":"2026-07-04T00:09:14.758580Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.07310/citation-record","integrity":"/paper/2506.07310/integrity","json":"/paper/2506.07310/citation-record.json","paper":"/paper/2506.07310"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:15.698049Z","title":"Drivetrack: A benchmark for long-range point tracking in real-world videos","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.698049Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:8efc16a565d6af1f2bf0b14d54cfc1bf6d6710c1543864c34f75e2147b15efa2","observation_id":"d8383de8-af9c-45f5-8794-b178d37aa740","resolution":{"observed_at":"2026-08-07T05:42:15.698049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.463177Z","title":"Context-pips: Persistent inde- pendent particles demands context features","venue":null,"work_id":"aec2e1ef-4ae7-4171-91e6-4bd8a3c048bd","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.703644Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:1c9c63334bfea57f8146aed971c3bc709e41cbc9b445edd124b881b9201f81d1","observation_id":"3c84f135-d45d-4faf-b3e2-ae9aabd96d7c","resolution":{"observed_at":"2026-08-07T05:42:16.466166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.453616Z","title":"Creatures great and SMAL: Recovering the shape and motion of animals from video","venue":null,"work_id":"a1e00145-3926-47cb-becd-ee631231f383","year":2018},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.706894Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:722900b6630306925c67546f0bbd79aa6e4412a04d8a9d77a98fdb59317dbc87","observation_id":"3bae1ebb-66cd-45ce-b855-ea24b8486ebf","resolution":{"observed_at":"2026-08-07T05:42:16.457491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.444476Z","title":"Large displacement optical flow: descriptor matching in variational motion estimation","venue":null,"work_id":"4577e0c5-2203-4c7e-a67b-ab013bd3ceb6","year":2010},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.710352Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:6e743982b7d601305213d30b8f4c35ffabc997910bac8bd2f53f98a97e7fe5e4","observation_id":"34721e1e-645d-457b-82a4-53e4d2102f62","resolution":{"observed_at":"2026-08-07T05:42:16.447661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.434507Z","title":"Flowtrack: Revisiting optical flow for long-range dense tracking","venue":null,"work_id":"360512b4-2d34-4e64-aeec-566a60088f86","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.713701Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:2bc2b966f72f0f70ddca951f8966cd7eb08db7450bb3075dc6cc452c754c94fe","observation_id":"c4579f96-903a-4d3a-ba46-30509acbcf7e","resolution":{"observed_at":"2026-08-07T05:42:16.437852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.423438Z","title":"Local all-pair correspondence for point tracking","venue":null,"work_id":"6ee011f1-b15d-4fe1-a1ef-53683025fa1c","year":2025},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.717456Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:8402f4d1001a7c7de2c559dfc658c6d34c691908e1aea370d6c6628e28e7579d","observation_id":"50c49f6a-c2b0-41e2-9271-4e764c06f1b7","resolution":{"observed_at":"2026-08-07T05:42:16.426861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.414404Z","title":"Dense long-term motion estimation via statistical multi-step flow","venue":null,"work_id":"56e8d86c-1a44-476d-aabd-1de5181f0cc3","year":2014},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.720740Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:691e1534e365e89a5c54c8ab8276c122b52b7a75070a24746d97ce8915340f5a","observation_id":"5755ed79-993d-4389-9c71-c3cdda1b648f","resolution":{"observed_at":"2026-08-07T05:42:16.417416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.405881Z","title":"Multi-reference combinatorial strategy towards longer long-term dense motion estimation","venue":null,"work_id":"ec7d760d-0818-468d-b690-0e322ea0f0ae","year":2016},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.724210Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:63ff820f8978c5e491b27a65e47fbf285ef448a29886c395eeb173b7cf2f8562","observation_id":"fcbb9b7c-85fe-4e16-b226-75095d6b3e21","resolution":{"observed_at":"2026-08-07T05:42:16.408988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.397346Z","title":"From optical flow to dense long term correspon- dences","venue":null,"work_id":"ab72c0c0-f3b7-4a50-92aa-cef2ac189922","year":null},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.727135Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:8f41623686dc7c99c1e8c630d10bd2f6e48f7df1cce9cad7ea5e12dc29e4027f","observation_id":"26473530-6e9e-4b87-a77d-3c46b268c468","resolution":{"observed_at":"2026-08-07T05:42:16.400415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04592","last_updated":"2024-12-05T20:12:29Z","snapshot_observed_at":"2026-07-06T20:02:30.984571Z","submitted_at":"2024-12-05T20:12:29Z","title":"EgoPoints: Advancing Point Tracking for Egocentric Videos","version":1},"cited_work":{"arxiv_id":"2412.04592","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04592","snapshot_observed_at":"2026-08-07T05:42:15.947558Z","title":"EgoPoints: Advancing Point Tracking for Egocentric Videos","venue":"cs.CV","work_id":"dba9138d-2a2f-4229-aa88-1bad84080589","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.730161Z"},"links":{"cited_paper":"/paper/2412.04592","citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:8d30d6a1200b569094271fdbaeb4c0bc32058a2915915ad0b14219a571cf77d8","observation_id":"d13be171-ce1a-4c8c-aa68-a248b344cda1","resolution":{"observed_at":"2026-08-07T05:42:15.953631Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.388716Z","title":"TAP-Vid: A benchmark for tracking any point in a video","venue":null,"work_id":"49872c74-8565-4ae6-a5cc-fc3f4e297447","year":null},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.733357Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:61a2e1938f0eba8c526467e39b8be85f56c66a61390322187b3d89d24e93d643","observation_id":"f2589e64-5e9d-4b7d-a320-9d0483b2c1b9","resolution":{"observed_at":"2026-08-07T05:42:16.391799Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.379398Z","title":"TAPIR: Tracking any point with per-frame initialization and temporal refinement","venue":null,"work_id":"54047473-e12e-4287-af4c-786664c12ed1","year":2023},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.736980Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:f71cf956434db8673d19637aeb5ac9b9f3627c4b13d3ba98ec03d8990ce1fa26","observation_id":"f1d3e972-6618-4906-8291-866f05d136de","resolution":{"observed_at":"2026-08-07T05:42:16.383107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.369908Z","title":"Bootstap: Bootstrapped training for tracking-any-point","venue":null,"work_id":"7d37ebc0-555f-47ba-ab7b-80e603f854d8","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.740679Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:27a49535b79faabfe58f44ab88736f1205f7c569dfbe5afc67fdad9d77f618b3","observation_id":"bd311069-b363-438d-b316-2d0eaa983e80","resolution":{"observed_at":"2026-08-07T05:42:16.372858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.360024Z","title":"Flownet: Learning optical flow with convolutional networks","venue":null,"work_id":"9de393b3-21d1-4c99-b839-2f874a06e0c4","year":2015},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.743658Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:510e760f1ce7bc3d3e5f10d2d8b16dbccdf6f1b5c8139e4b3bf97fe57aec0d7a","observation_id":"7b48119d-f87d-4158-b6d9-80cf9fcb1d7c","resolution":{"observed_at":"2026-08-07T05:42:16.363167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.350617Z","title":"Vision meets robotics: The kitti dataset","venue":null,"work_id":"ad57f0ed-b87a-4976-b03a-9f8e9d3fbb2b","year":2013},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.746646Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:a829a773f9897e0334624d59f7bedfbbb541021b0bdcfd9c4e96001632589c06","observation_id":"63c4e7de-f716-4fec-a61f-3eb2ac149a41","resolution":{"observed_at":"2026-08-07T05:42:16.353711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.341619Z","title":"The perception of the visual world","venue":null,"work_id":"957d7f20-3f3b-4fa1-bb34-eeef284d91f5","year":1950},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.749532Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:301ec13be94613c2612b65e9739bc1e752aef484111ec5b298f7cd290770a084","observation_id":"5f1085a8-d1f3-40e7-b449-fb6a104f27e6","resolution":{"observed_at":"2026-08-07T05:42:16.344970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.331979Z","title":"Kubric: A scalable dataset generator","venue":null,"work_id":"d04d894a-24bf-4a7b-991f-66312f3a7714","year":2022},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.752245Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:9da3d4a791661c6aeddf18ce183eaf17f5e386faef109d9c5e66c76b193ef8b0","observation_id":"94f6b30e-6f41-4529-bf1e-db894a4dd309","resolution":{"observed_at":"2026-08-07T05:42:16.335181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.321691Z","title":"TAG: Tracking at any granularity","venue":null,"work_id":"486a0e72-8fde-46d1-8a6f-5db724724447","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.755368Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:313cdc59cde7371d12efdcca040722cfea0bbebae79e07514395586b38139f4b","observation_id":"5c2187d5-40e1-4934-ba65-a9ca112bad33","resolution":{"observed_at":"2026-08-07T05:42:16.325309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.311886Z","title":"Particle video revisited: Tracking through occlusions using point trajectories","venue":null,"work_id":"69203283-a365-4807-b809-d29b95a80a49","year":2022},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.758174Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:92cea25d7708ecb7af71380a6beed7aa54999846c184c7f77a5e5d2f03aff432","observation_id":"eaf0ab09-c81b-4dda-8e7f-85bfaba048a7","resolution":{"observed_at":"2026-08-07T05:42:16.315351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.301492Z","title":"Deep residual learning for image recognition","venue":null,"work_id":"6bba5649-2a55-4985-aa06-905ee2a2554d","year":2016},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.761389Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:411717bfa502ac3f9066008c965391c65331d7421f1f9f7d7219c5c349355af2","observation_id":"0a00f610-81fd-4edd-9867-00e59ff3cacf","resolution":{"observed_at":"2026-08-07T05:42:16.305319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.292374Z","title":"Determining optical flow","venue":null,"work_id":"4085cc77-a84f-4437-bea8-1ee55dcfc915","year":1981},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.765152Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:37bb859f0b0f20414d043ce3b37d2b6be379ae2e9865578a55fb0dffee98f2e4","observation_id":"905311e2-9621-495e-97aa-3e69932c4b22","resolution":{"observed_at":"2026-08-07T05:42:16.295319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.282027Z","title":"Flownet 2.0: Evolu- tion of optical flow estimation with deep networks","venue":null,"work_id":"1e57a79c-a4fa-461f-be23-05f08d1d1732","year":null},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.769221Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:e6ae2bf2c7872a1faf5f5e1e6ce43f4edcb2e9cc2740568be9e75dc555edb143","observation_id":"d13904e7-5c28-4bba-a257-623b20e99122","resolution":{"observed_at":"2026-08-07T05:42:16.285406Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:15.772465Z","title":"Dy- namicstereo: Consistent dynamic depth from stereo videos","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.772465Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:7f0f9b4674e19480f61f5252ac50eac428778929de76f2184af91891e81fad96","observation_id":"f9f16d06-e76f-4bd2-9792-5c7c51320b5f","resolution":{"observed_at":"2026-08-07T05:42:15.772465Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.11831","last_updated":"2024-10-15T17:56:32Z","snapshot_observed_at":"2026-08-03T21:35:04.144048Z","submitted_at":"2024-10-15T17:56:32Z","title":"CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.11831","snapshot_observed_at":"2026-08-07T05:42:15.776281Z","title":"Co- tracker3: Simpler and better point tracking by pseudo- labelling real videos","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.776281Z"},"links":{"cited_paper":"/paper/2410.11831","citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:e6a119c0376d630367bca272e9c7460af955e6125831b98a2fd2cb3fa3467d89","observation_id":"e5b244db-c393-4185-b56d-ffd7b87b73e5","resolution":{"observed_at":"2026-08-07T05:42:15.776281Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.266960Z","title":"Co- Tracker: It is better to track together","venue":null,"work_id":"27ebf66f-a95a-48a7-80c0-9c5e9358de2a","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.780100Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:eafd14953270d036b9daf3c531a16b75d378820640db23b377ff27afabd90a5c","observation_id":"01d402c9-9340-4e2c-a5aa-e575a417b0e8","resolution":{"observed_at":"2026-08-07T05:42:16.269786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.258340Z","title":"The HCI benchmark suite: Stereo and flow ground truth with uncertainties for urban autonomous driving","venue":null,"work_id":"2798d5da-ce0a-4f16-8527-2d90620a23b0","year":2016},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.782937Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:e23dd141d7f9ed7e3d2d8f2e8b82aeadedd458afccd266871238f99536731c4b","observation_id":"1992e633-fe70-4d4f-9e4d-9a7aa38e6421","resolution":{"observed_at":"2026-08-07T05:42:16.261508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.248703Z","title":"Dense optical tracking: connecting the dots","venue":null,"work_id":"80a48704-3dd4-47dd-9940-ca8e7fa5ee9d","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.785685Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:b6ee6084c90d72bbe5af3132e60e41fdeb57962819dd071938f1ed67cb755d0a","observation_id":"bfbe02dd-e9ee-4f10-b1ad-3067cd365803","resolution":{"observed_at":"2026-08-07T05:42:16.251809Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.240118Z","title":"Beyond pick-and-place: Tackling robotic stacking of diverse shapes","venue":null,"work_id":"3dd14382-fead-4e6a-8272-d9b3a49a21a7","year":2021},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.788650Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:5c91745a332265b349972eacf942d7bad218574372212a835a356b1425962c23","observation_id":"9103b17b-1b80-4fed-be1a-0c8845342721","resolution":{"observed_at":"2026-08-07T05:42:16.243360Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.230972Z","title":"TAPTRv2: Attention-based position update improves tracking any point","venue":null,"work_id":"70482fd5-7ba6-4b09-8a4e-656c873b848a","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.791319Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:19db587335aea7719d28f60ca1f7f7bf339c70ccad0246a9f63abb79711cc277","observation_id":"1c136b25-c0c6-44b0-80d0-1d089f9fd948","resolution":{"observed_at":"2026-08-07T05:42:16.234515Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.221793Z","title":"TAPTR: Tracking any point with transformers as detection","venue":null,"work_id":"f2e07873-52e0-4e76-8f41-7495e1b7a72f","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.794134Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:e24b33c6c56283e93c4fe5a65276ab2616820ca57f075ff96e5b7e9a5d99c45a","observation_id":"e03ba539-937d-49eb-9ebc-4cb6e5c3a20b","resolution":{"observed_at":"2026-08-07T05:42:16.225130Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.213692Z","title":"A convnet for the 2020s","venue":null,"work_id":"5b234057-944b-495b-92e1-b672ef31dfce","year":2022},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.796808Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:9533b9d8ab5138ea4594b2406edaf37eaecfe134400045312d18fc841430faad","observation_id":"91358c2f-b288-4c1a-87cd-6bb3b078176c","resolution":{"observed_at":"2026-08-07T05:42:16.216418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.204672Z","title":"An iterative image registration technique with an application to stereo vision","venue":null,"work_id":"cd36716c-2859-41e8-8c8e-508cebf92fc3","year":1981},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.799646Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:666ebc34e21b74588e83456761083641b0e9182426b132a4f7438231534889ac","observation_id":"e986d045-1c74-4069-9d81-ac9ab0403f4a","resolution":{"observed_at":"2026-08-07T05:42:16.208174Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.196249Z","title":"Pretraining boosts out-of-domain robustness for pose estimation","venue":null,"work_id":"ed9994b8-b3e5-4461-b86c-74ca28c8fce6","year":2021},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.802658Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:9929058099c271b60c7c7e5ca08ec0a87f3be05cd16c9161dce88982a7044451","observation_id":"ab41ce3f-3628-410b-8a99-3783452df143","resolution":{"observed_at":"2026-08-07T05:42:16.199286Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.187603Z","title":"A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation","venue":null,"work_id":"5a5504cb-682f-4edd-a0fd-f055107d5289","year":2016},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.805860Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:c62717a4696222eb55e743c0cd65f5fd85ed67b8eb63bee32e038076e2d09f06","observation_id":"3044c2a2-17c5-41b8-8a0d-6595d10c3245","resolution":{"observed_at":"2026-08-07T05:42:16.190886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.179279Z","title":"Spring: A high-resolution high- detail dataset and benchmark for scene flow, optical flow and stereo","venue":null,"work_id":"5f45ceca-7d1e-4f27-a5bc-93f1927c81d9","year":2023},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.808782Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:7eb637d039e4a211852d259bb6eacd1a3254a2abee12cf5846454095ba9f9c0f","observation_id":"fdb29161-405d-4ad2-aff0-ec538aaa30b4","resolution":{"observed_at":"2026-08-07T05:42:16.182278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.171228Z","title":"Mft: Long-term tracking of every pixel","venue":null,"work_id":"7d4f079d-0612-40b1-bf70-49dafbbc681e","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.811910Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:4593f2b63efea4bbce21fe79a9582e0b1455c90d152a0b0d167053a626328ec4","observation_id":"1d1fa616-ea17-4ca1-82a3-bef91f5c75f6","resolution":{"observed_at":"2026-08-07T05:42:16.174044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.161523Z","title":"DELTA: Dense efficient long-range 3d tracking for any video","venue":null,"work_id":"cff8d54e-c8ce-4ccc-bec3-64a1f0e1d6c7","year":2025},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.814839Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:1378c2a45f8ab0558ee7cb6ed6f3c616911bbdc2b587368c77111d51f8c2c59e","observation_id":"e55dcf5d-9b31-4d58-98da-b6775558d942","resolution":{"observed_at":"2026-08-07T05:42:16.165350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.152451Z","title":"Optic flow: a history","venue":null,"work_id":"dc7dbe75-65e8-4c35-abad-f16498e69cce","year":2021},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.817728Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:ca92a715852eef7ef3e607e99f430729404bc90874ef86350dd3508c662ae97d","observation_id":"dcbbd702-dbd4-4b5e-9201-b7767ae44282","resolution":{"observed_at":"2026-08-07T05:42:16.155547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.143752Z","title":"Playing for benchmarks","venue":null,"work_id":"eabe0bae-54c5-4fdb-a327-a98a0b485445","year":2017},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.820446Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:7aee7e18f8c4f74f3882ab4680ee89c276562c439fd862d2de42538124fa090a","observation_id":"778ba453-c475-4e6d-9eea-0d44e69e5a5b","resolution":{"observed_at":"2026-08-07T05:42:16.146712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.135155Z","title":"Sand and S","venue":null,"work_id":"3aa66c6f-7e43-49aa-9ec5-2058ca82783f","year":2006},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.823166Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:92d8c938c7577e570ad35abd540c8d9a6c0c1566e872d3567dab57b2bca180fd","observation_id":"7542056f-9cec-4d24-b08a-8fe5e2cc8b9d","resolution":{"observed_at":"2026-08-07T05:42:16.137976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.126433Z","title":"Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network","venue":null,"work_id":"07e993a1-ea44-4539-963a-e4ad7da5330f","year":2016},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.826663Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:56e31971a8f5aa454c014ca7a543050f165681faf80932fd81b229cd7ad0e2d9","observation_id":"2fc6913d-fcd5-4b4f-9551-9c09a8779c15","resolution":{"observed_at":"2026-08-07T05:42:16.129399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.117237Z","title":"PWC-Net: CNNs for optical flow using pyramid, warping, and cost volume","venue":null,"work_id":"055f1b6a-0b4f-4af1-8cf6-6497f20aecce","year":2018},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.829598Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:6f1756a87322c50ac2e57727f53b04afb00a9053466c68ed0005b659a5aa83ce","observation_id":"e26f71bb-75a8-4add-baaa-3959645c0972","resolution":{"observed_at":"2026-08-07T05:42:16.120300Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.108440Z","title":"Autoflow: Learning a better training set for optical flow","venue":null,"work_id":"118dfab9-5923-4754-a63f-1f5c64a7cc4e","year":2021},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.832301Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:53c58504027d39a226c2347b1dfef7d1fc139a4c5aa7751e47cae41a7d82d92a","observation_id":"85fbe524-bd5b-4ca5-a1f3-86676e1520c6","resolution":{"observed_at":"2026-08-07T05:42:16.111442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.098300Z","title":"Re- fining pre-trained motion models","venue":null,"work_id":"a246436e-450e-4c0d-8dc9-4cfc0391da81","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.835383Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:9fc639887fa37166eedcae10810b5f08f1089f48015bdd59346c866b68d6cd1d","observation_id":"0abccda5-f757-41cd-a5de-512c8d5c2172","resolution":{"observed_at":"2026-08-07T05:42:16.101353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.089827Z","title":"Dense point trajectories by GPU-accelerated large displace- ment optical flow","venue":null,"work_id":"4796f936-539f-44a5-99f4-6b09814a6c1c","year":2010},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.837994Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:1d4f33db887a159ea0a3e6ede5dffd522f64774d1e0f6227a842587785a549cd","observation_id":"7af4a607-98df-459f-be39-dda5d9765da2","resolution":{"observed_at":"2026-08-07T05:42:16.092968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.081458Z","title":"Tracking pedestrian heads in dense crowd","venue":null,"work_id":"c44555b0-eac1-4fc4-bf02-8a32f8b66207","year":2021},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.840681Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:a1d6b7a012ffe512b0209e7edb4c906766010435dc207b876ce60855b883f75b","observation_id":"93a33e7c-fabd-4fdc-b8a9-b6d8b650b4be","resolution":{"observed_at":"2026-08-07T05:42:16.084257Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.073557Z","title":"RAFT: Recurrent all-pairs field transforms for optical flow","venue":null,"work_id":"e1a2ef7e-7b89-443f-b70e-8fe560a6fbca","year":2020},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.843586Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:aafbf9933247c68dbd4404414a20a3c9b55b9f5db2fb4f9854b31d01bd8a02df","observation_id":"8eca5304-037d-4c9b-a34e-231aef32acc4","resolution":{"observed_at":"2026-08-07T05:42:16.076433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2105.01601","last_updated":"2021-06-11T09:36:50Z","snapshot_observed_at":"2026-08-06T23:46:59.006674Z","submitted_at":"2021-05-04T16:17:21Z","title":"MLP-Mixer: An all-MLP Architecture for Vision","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.01601","snapshot_observed_at":"2026-08-07T05:42:15.846285Z","title":"Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lu- cas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, and Alexey Dosovitskiy","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.846285Z"},"links":{"cited_paper":"/paper/2105.01601","citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:2866051b6f0888375374d8dfcde68f60f53f119502df3d0e9a34423591445c02","observation_id":"3dfdcaae-078a-49e3-af05-5a8ca0f587e5","resolution":{"observed_at":"2026-08-07T05:42:15.846285Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.065634Z","title":"Detection and tracking of point","venue":null,"work_id":"d912934b-5d30-4dee-8bda-1fcefd572b0a","year":1991},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.849353Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:f2781ba85ec10769ded1ecc654e3cbe3840ca5786f8b4ed5405fab36d32f2944","observation_id":"86448154-1e5c-4486-be5d-f6f920890765","resolution":{"observed_at":"2026-08-07T05:42:16.068291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.057022Z","title":"Dense trajectory fields: Consistent and efficient spatio-temporal pixel tracking","venue":null,"work_id":"f0ce97d6-c271-4274-93db-42aceae74097","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.852337Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:5a651520a4cb126ef1c6a9e99e233223d3276e3587cd6cedce6a2a97c91263c5","observation_id":"935556e4-36f1-4e12-8c69-6cec807d1497","resolution":{"observed_at":"2026-08-07T05:42:16.060215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.048038Z","title":"Attention is all you need","venue":null,"work_id":"bfa66504-f9bc-45ef-8d89-0cc07276e9be","year":2017},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.855184Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:312f108f7113e0c4d09f6a434fcef3b89d6db1b62555052194fee5312892bc80","observation_id":"6eff8145-d987-4207-ac97-65476cb293aa","resolution":{"observed_at":"2026-08-07T05:42:16.051053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.037948Z","title":"RoboTAP: Tracking arbitrary points for few-shot visual imitation","venue":null,"work_id":"637316ab-94e0-4474-8ab0-4c48b6bdb586","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.858527Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:fbf1be087738627e6a93c195b702c289288cadb191b917005447f55f4dcc152e","observation_id":"a83dd5a8-2ce6-4f01-9410-63cf7bc14044","resolution":{"observed_at":"2026-08-07T05:42:16.041287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.028327Z","title":"TartanAir: A dataset to push the limits of visual slam","venue":null,"work_id":"67bd363e-30d1-4e2a-889e-137f3b6368d0","year":2020},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.862018Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:45f6f26edf4592656e9e902f8ad0970b0bc7669797219a490b53a6ea6ac97af9","observation_id":"2294c584-5d80-4e71-b299-0e8727a43a35","resolution":{"observed_at":"2026-08-07T05:42:16.031461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.018681Z","title":"Sea-raft: Simple, efficient, accurate raft for optical flow","venue":null,"work_id":"87f2b0c1-fcf2-48cd-8e89-3f2e70318b8d","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.864901Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:211380db5f29ddbf72f5a0589356bf5d1dad611c6b3d237a44eeec81a0b30391","observation_id":"717d4be9-6ebb-4d4e-9870-d09a3b683d83","resolution":{"observed_at":"2026-08-07T05:42:16.022359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:16.009295Z","title":"Accflow: Backward accumulation for long-range optical flow","venue":null,"work_id":"eafdc82e-5ab4-4f4d-b36a-d1c4ecc71fe4","year":2023},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.867807Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:76cff4dd30fa0150976e8427a5089b35101acea1d8f7a6538281f5011a868479","observation_id":"f2d9bcc0-1780-4cf4-bda8-770d3122c484","resolution":{"observed_at":"2026-08-07T05:42:16.012489Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:15.999910Z","title":"Spatialtracker: Tracking any 2d pixels in 3d space","venue":null,"work_id":"c73c96be-4fc1-4723-8481-61f7864d404e","year":2024},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.870737Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:1fbc8dd674d7e71224d6ecfcda188df9820d359c5b9520f0b1e9c4567c8bef88","observation_id":"5d36a40f-7147-4b09-b0b2-12445d6853fe","resolution":{"observed_at":"2026-08-07T05:42:16.003299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:15.989978Z","title":"Gmflow: Learning optical flow via global matching","venue":null,"work_id":"c0e45fe7-df88-4132-be17-036a2d6decda","year":2022},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.873655Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:a2aec7ee01e2cb24c99ac0405ca46ef323da18c21ed8bb3d686379ba36ad1f98","observation_id":"ae132179-af28-4c3e-85cb-8deae08dcd09","resolution":{"observed_at":"2026-08-07T05:42:15.993219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:15.980998Z","title":"Accurate optical flow via direct cost volume processing","venue":null,"work_id":"965a4220-3686-43fe-86b7-ca5006f9ec6f","year":2017},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.876500Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:a6cf221a68d0e0c140d6eca40df9bf2bdf5ad56a849818319ebdafa90a8e50d7","observation_id":"069e341f-9b01-4a4d-88bd-cd87d2cc438b","resolution":{"observed_at":"2026-08-07T05:42:15.983941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:15.970410Z","title":"Harley, Bokui Shen, Gordon Wet- zstein, and Leonidas J","venue":null,"work_id":"274af748-f9ab-4054-994e-fb4bfbc31637","year":2023},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.879385Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:1eed9e2633a14cb760d05325950a9eba3547fd73b4e085f66218ce3b4c865860","observation_id":"a1f7037f-172b-48bb-9664-0ae650f85615","resolution":{"observed_at":"2026-08-07T05:42:15.973869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.05579","last_updated":"2025-04-14T12:17:03Z","snapshot_observed_at":"2026-08-07T16:07:45.648626Z","submitted_at":"2025-04-08T00:28:42Z","title":"TAPNext: Tracking Any Point (TAP) as Next Token Prediction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.05579","snapshot_observed_at":"2026-08-07T05:42:15.882789Z","title":"TAPNext: Tracking any point (TAP) as next token prediction","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.882789Z"},"links":{"cited_paper":"/paper/2504.05579","citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:58433b94f222725d838061f6df981dfc3146ae35459f7f9ab31cda8453a2fa51","observation_id":"54e95aa7-396d-4e38-8ad6-68945d178ef8","resolution":{"observed_at":"2026-08-07T05:42:15.882789Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:42:15.961250Z","title":"space- time","venue":null,"work_id":"a6b79291-dd0c-4ccf-b3fa-7a25d1049e57","year":null},"citing_paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T05:42:15.886444Z"},"links":{"citing_paper":"/paper/2506.07310"},"observation_digest":"sha256:04179a66f68bf5b83ec72ca0a708215e7eb493f912de8931642455f525d58b44","observation_id":"a72e7afa-b5a1-49ec-a434-a2a8519884bc","resolution":{"observed_at":"2026-08-07T05:42:15.964291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.07310","last_updated":"2025-08-01T18:44:17Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T05:34:25.906219Z","submitted_at":"2025-06-08T22:55:06Z","title":"AllTracker: Efficient Dense Point Tracking at High Resolution"},"reference_resolution":{"displayed":61,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":1,"verified_fuzzy":55},"total_outbound_references":61},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 4 inbound Pith citation observations for arXiv:2506.07310."}