{"as_of":"2026-08-22T03:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d00a347a2021559e472a2960bacfc233155e2bce1bfbbd72af5a1d34132de813","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:40:45.276257Z","state":"measured"},{"denominator":25,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":25,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.06692/citation-record","integrity":"/paper/1908.06692/integrity","json":"/paper/1908.06692/citation-record.json","paper":"/paper/1908.06692"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:40:45.645603Z","title":"Cnn in mrf: Video object segmentation via inference in a cnn-based higher-order spatio-temporal mrf","venue":null,"work_id":"3db78a03-b0ae-4865-b374-d26cf26968dd","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.169924Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:90503fa9ca2c5c5cf661ba870f35f7a3be631740c3de8b20aba04252fb1119b6","observation_id":"d45d52d7-213e-4379-9d34-578a08c886d7","resolution":{"observed_at":"2026-08-14T12:40:45.650911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.630684Z","title":"One-shot video object segmentation","venue":null,"work_id":"4415a210-8333-4086-b99f-62ceb68c9e41","year":2017},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.174721Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:365eec15e691e7c3f18048e8f0a7b00068d23af2b1b9873bce9bd6c083e7cbbb","observation_id":"629dd9a1-d5d9-4a4b-8edb-fe9ebf11e19f","resolution":{"observed_at":"2026-08-14T12:40:45.635258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1812.08008","last_updated":"2019-05-30T23:46:18Z","snapshot_observed_at":"2026-08-20T13:31:43.661125Z","submitted_at":"2018-12-18T18:50:33Z","title":"OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.08008","snapshot_observed_at":"2026-08-14T12:40:45.179567Z","title":"Openpose: realtime multi-person 2d pose estimation using part afﬁnity ﬁelds","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.179567Z"},"links":{"cited_paper":"/paper/1812.08008","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:1f0f885fe8c691aa4b69179ef140a5b0718243fe94f9f9e58ba825cc43375914","observation_id":"6214ba17-9cff-4d9d-abf6-54ffc8d32ad0","resolution":{"observed_at":"2026-08-14T12:40:45.179567Z","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":"2026-08-14T12:40:45.617190Z","title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs","venue":null,"work_id":"9dc694b7-81e9-4d8d-8cbb-c85533017f91","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.184660Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:09bc2de4646218de1e1c6bcb84b2dfd576564d6bb4fc900d109b2879f24f8199","observation_id":"21b26963-77e5-450b-a5ec-93f5fafa13d7","resolution":{"observed_at":"2026-08-14T12:40:45.621452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.603695Z","title":"Blazingly fast video object segmentation with pixel-wise metric learning","venue":null,"work_id":"f68c4aa5-defd-4cde-a15e-532c71c82fe8","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.189758Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:ddbd3e22b21ac4bb0d854a113ec5c1f895d5c3fb017fdf1cc7e689c5e69c0c57","observation_id":"31623a21-c66a-4c2c-b293-6fe477a67da9","resolution":{"observed_at":"2026-08-14T12:40:45.608057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.589688Z","title":"Segﬂow: Joint learning for video object segmentation and optical ﬂow","venue":null,"work_id":"b7e88ac0-5412-45fe-a47d-4c6bd91cd6bc","year":2017},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.194308Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:1d59e1e9c2fc6755f748a9aba727fdd5cba1b67024a81b7b952832ce6d7f81b8","observation_id":"2fb77764-79f0-4a29-aaf1-dd21abc3fc99","resolution":{"observed_at":"2026-08-14T12:40:45.594377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.575855Z","title":"Fast and accurate online video object segmentation via tracking parts","venue":null,"work_id":"74068b43-122b-4faa-a059-8395448eb828","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.199150Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:3472fa4b9ca0fc399dd9fe8b096abcddea3a5a5b7cb91060100f83c2b3d7e374","observation_id":"12d3e1a3-b1ec-4a63-a6dc-eeeaf1be14f8","resolution":{"observed_at":"2026-08-14T12:40:45.580285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.02551","last_updated":"2017-08-08T16:32:48Z","snapshot_observed_at":"2026-08-16T11:01:29.449473Z","submitted_at":"2017-08-08T16:32:48Z","title":"Semantic Instance Segmentation with a Discriminative Loss Function","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.02551","snapshot_observed_at":"2026-08-14T12:40:45.203057Z","title":"Semantic instance segmentation with a discriminative loss function","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.203057Z"},"links":{"cited_paper":"/paper/1708.02551","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:9c4f3d5d734e6119a10117919efcf501cf8641cea57476b2a7fde861cf7a988d","observation_id":"ff26ee59-dc6f-4598-9b96-45d10eacc0c3","resolution":{"observed_at":"2026-08-14T12:40:45.203057Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:40:45.207447Z","title":"Imagenet: A large-scale hierarchical image database","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.207447Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:9395de138c69f2111e83d9ac5fe8b4ac5259a0d8c0de972c80684b7c724bdc77","observation_id":"d0720bda-a564-4aed-a287-042c76003fe7","resolution":{"observed_at":"2026-08-14T12:40:45.207447Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:40:45.211602Z","title":"Fast r-cnn","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.211602Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:9edf2943bd6aefd37fccaef1118b16841c9db6fa2a667a275d1db0d188ecccfb","observation_id":"dc71a0b6-c55f-4662-bd42-159c0ed5faf0","resolution":{"observed_at":"2026-08-14T12:40:45.211602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1704.04861","last_updated":"2017-04-17T03:57:34Z","snapshot_observed_at":"2026-08-20T09:32:02.065929Z","submitted_at":"2017-04-17T03:57:34Z","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1704.04861","snapshot_observed_at":"2026-08-14T12:40:45.215860Z","title":"Mobilenets: Efﬁ- cient convolutional neural networks for mobile vision applications","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.215860Z"},"links":{"cited_paper":"/paper/1704.04861","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:d690057093e7b46588d9dfb37035ed9823db5223a30b5c258a2b5c3d612ff8b0","observation_id":"afdd8284-9d0e-42b4-a70b-f6f835343dbb","resolution":{"observed_at":"2026-08-14T12:40:45.215860Z","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":"2026-08-14T12:40:45.545897Z","title":"Path aggregation network for instance segmentation","venue":null,"work_id":"a04b3299-3e35-4d30-87ec-2aefd1c3424b","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.220449Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:1b08c73638cd1c4183bb0471ea3a8540269ec12bd0e0a6d6f5c30beeb1b5bdea","observation_id":"779ab089-3a95-4fdd-b765-9f509f3bb63a","resolution":{"observed_at":"2026-08-14T12:40:45.550206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1901.03796","last_updated":"2019-01-12T04:43:17Z","snapshot_observed_at":"2026-08-14T17:31:59.885967Z","submitted_at":"2019-01-12T04:43:17Z","title":"Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes","version":1},"cited_work":{"arxiv_id":"1901.03796","doi":null,"metadata_source":"pith","pith_arxiv_id":"1901.03796","snapshot_observed_at":"2026-08-14T12:40:45.414613Z","title":"Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes","venue":"cs.CV","work_id":"90a1ce52-3eb0-4da8-a36e-a52ab4907ab8","year":2019},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.224749Z"},"links":{"cited_paper":"/paper/1901.03796","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:57fafcdf6f14cc1b59489efeed70791748c30e61b7774f90d3a55d33e2cb7eb4","observation_id":"7502c6ab-cc83-46d2-b311-c1d46d9b4360","resolution":{"observed_at":"2026-08-14T12:40:45.419060Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.229076Z","title":"Fully convolutional networks for semantic segmentation","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.229076Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:541a414a429ec33367bb43d22043bf74b2b81a869a9c43da69dd383c1ac66f0b","observation_id":"7f31dfdf-dc2b-462f-bd85-7fe1d4e1edad","resolution":{"observed_at":"2026-08-14T12:40:45.229076Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.09190","last_updated":"2018-11-03T17:35:06Z","snapshot_observed_at":"2026-08-14T18:48:15.582147Z","submitted_at":"2018-07-24T15:42:45Z","title":"PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation","version":2},"cited_work":{"arxiv_id":"1807.09190","doi":null,"metadata_source":"pith","pith_arxiv_id":"1807.09190","snapshot_observed_at":"2026-08-14T12:40:45.396396Z","title":"PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation","venue":"cs.CV","work_id":"396baf68-4cb8-40f6-aa64-df89ed15fb3f","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.233166Z"},"links":{"cited_paper":"/paper/1807.09190","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:f73826bbaa8739bc77c67882f3551083277161ee904c151bc8ed4a2eba875824","observation_id":"0c963b23-722a-4ca6-8e58-d146a4ac8814","resolution":{"observed_at":"2026-08-14T12:40:45.401255Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.06031","last_updated":"2018-05-16T12:16:48Z","snapshot_observed_at":"2026-08-17T06:47:33.973222Z","submitted_at":"2017-09-18T16:28:02Z","title":"Video Object Segmentation Without Temporal Information","version":2},"cited_work":{"arxiv_id":"1709.06031","doi":null,"metadata_source":"pith","pith_arxiv_id":"1709.06031","snapshot_observed_at":"2026-08-14T12:40:45.377224Z","title":"Video Object Segmentation Without Temporal Information","venue":"cs.CV","work_id":"730657bb-7359-40e6-b783-1fa8ea99913d","year":2017},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.237911Z"},"links":{"cited_paper":"/paper/1709.06031","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:a1c2ea5de0c23f7c60f7f64471d68603cf499747b674d649f212f7ac7824871f","observation_id":"d4f8529f-4f24-4270-bdf8-c591ae559ed2","resolution":{"observed_at":"2026-08-14T12:40:45.381881Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.522848Z","title":"A benchmark dataset and evaluation methodology for video object segmentation","venue":null,"work_id":"69826787-bf6d-4581-ad59-5be2450bb11a","year":2016},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.242305Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:fe7f1174810b08867a61b67de09df234775203963ff50180644eff2fb3c74785","observation_id":"da2e581e-2133-4a81-a291-2a99b2c15f33","resolution":{"observed_at":"2026-08-14T12:40:45.527219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.509576Z","title":"Learning video object segmentation from static images","venue":null,"work_id":"4861c5a7-b312-466f-8975-273dca8fb57e","year":2017},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.246323Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:759a117bed622c5b56aada13fdff26f2412ccf4241e599df6d168fcc7c0ca105","observation_id":"858faf3d-f2fd-495e-ac18-af54bab2f109","resolution":{"observed_at":"2026-08-14T12:40:45.514046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.02767","last_updated":"2018-04-08T22:27:57Z","snapshot_observed_at":"2026-08-15T16:54:48.034047Z","submitted_at":"2018-04-08T22:27:57Z","title":"YOLOv3: An Incremental Improvement","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.02767","snapshot_observed_at":"2026-08-14T12:40:45.250353Z","title":"Yolov3: An incremental improvement","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.250353Z"},"links":{"cited_paper":"/paper/1804.02767","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:b48f96ec7329bd10a4844a8f60d08cef714474b423c3d0ff4b834a0988a5fa13","observation_id":"086115ad-2a7c-4b88-8f2c-5f581a82f96e","resolution":{"observed_at":"2026-08-14T12:40:45.250353Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.10289","last_updated":"2018-10-24T10:59:51Z","snapshot_observed_at":"2026-08-14T18:10:04.147485Z","submitted_at":"2018-10-24T10:59:51Z","title":"Mask Propagation Network for Video Object Segmentation","version":1},"cited_work":{"arxiv_id":"1810.10289","doi":null,"metadata_source":"pith","pith_arxiv_id":"1810.10289","snapshot_observed_at":"2026-08-14T12:40:45.345278Z","title":"Mask Propagation Network for Video Object Segmentation","venue":"cs.CV","work_id":"dd0db78c-4dee-480d-b1f0-4475c9e11521","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.254530Z"},"links":{"cited_paper":"/paper/1810.10289","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:aa65202eb69f412c9168f52150491c7b3ea205f755de6b69af922de3daabaff6","observation_id":"ac43b341-00c5-4cd2-9541-299c698445a9","resolution":{"observed_at":"2026-08-14T12:40:45.350107Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.09364","last_updated":"2017-08-01T15:18:18Z","snapshot_observed_at":"2026-08-19T12:17:12.685618Z","submitted_at":"2017-06-28T17:02:39Z","title":"Online Adaptation of Convolutional Neural Networks for Video Object Segmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.09364","snapshot_observed_at":"2026-08-14T12:40:45.259576Z","title":"Online adaptation of convolutional neural net- works for video object segmentation","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.259576Z"},"links":{"cited_paper":"/paper/1706.09364","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:d1b5d507c0e55415acd205cf3b96c8b733a40006836037f72d8a19e07147ad9a","observation_id":"6b16e352-f583-439b-9b55-9cd8b1435b75","resolution":{"observed_at":"2026-08-14T12:40:45.259576Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.05050","last_updated":"2019-05-05T03:49:18Z","snapshot_observed_at":"2026-08-14T17:44:38.674748Z","submitted_at":"2018-12-12T17:43:04Z","title":"Fast Online Object Tracking and Segmentation: A Unifying Approach","version":2},"cited_work":{"arxiv_id":"1812.05050","doi":null,"metadata_source":"pith","pith_arxiv_id":"1812.05050","snapshot_observed_at":"2026-08-14T12:40:45.310352Z","title":"Fast Online Object Tracking and Segmentation: A Unifying Approach","venue":"cs.CV","work_id":"5bae4761-6b76-4e8f-97db-9d76ffa65af6","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.263890Z"},"links":{"cited_paper":"/paper/1812.05050","citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:2c34e783ff0e1cbee4720dfea4b01d64d2b66f925cdaf3cb180342d793900119","observation_id":"4fc2b90c-3c42-4020-8604-8526cfb167fd","resolution":{"observed_at":"2026-08-14T12:40:45.316685Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.495840Z","title":"Fast video object segmentation by reference-guided mask propagation","venue":null,"work_id":"69a2064c-f9a0-4381-b8e9-b792be76c845","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.268295Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:0eb7af1a9966457f335d744994aea75ef0d271e6e6b232fa955ee58b2e93ddbd","observation_id":"30c2238f-3fc4-41ea-b575-709aaaa0378b","resolution":{"observed_at":"2026-08-14T12:40:45.500613Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.482376Z","title":"Holistically-nested edge detection","venue":null,"work_id":"92e25172-03e3-4ef4-8564-169d9a6b2051","year":2015},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.272292Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:621b51884d0043ec232c254486d00d959a347ad5db7ed22418fa3694d2300c94","observation_id":"9686cb5b-c170-4022-858a-4e46872f6027","resolution":{"observed_at":"2026-08-14T12:40:45.486756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-14T12:40:45.468748Z","title":"Efﬁcient video object segmentation via network modulation","venue":null,"work_id":"3fe37ebd-91da-4459-8c9d-d2fb2ced472a","year":2018},"citing_paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T12:40:45.276257Z"},"links":{"citing_paper":"/paper/1908.06692"},"observation_digest":"sha256:d8335997c507470bf8ceec5c4f6174ce223b11e8bc8d341300cafb0222f9307b","observation_id":"750bce59-379b-4c7d-9851-7a78914f5bcf","resolution":{"observed_at":"2026-08-14T12:40:45.473346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.06692","last_updated":"2019-08-20T01:24:35Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-20T18:01:07.852348Z","submitted_at":"2019-08-19T11:07:17Z","title":"In defense of OSVOS"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":5,"verified_fuzzy":12},"total_outbound_references":25},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:1908.06692."}