{"as_of":"2026-08-18T23:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4068b185e18b8c06010471fd73f43c578eee7c5703af7052916e2014997f011d","coverage":[{"denominator":63,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":63,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T15:44:08.365037Z","state":"measured"},{"denominator":63,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":63,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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/2411.13975/citation-record","integrity":"/paper/2411.13975/integrity","json":"/paper/2411.13975/citation-record.json","paper":"/paper/2411.13975"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T15:44:08.079604Z","title":"Frequency-tuned salient region de- tection","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.079604Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:305a901d97213d96cf3bb3ebcd3db53ddd48fbaa6e23f42349a8a5ddf9d1e591","observation_id":"a244aabf-9a9b-4f47-b783-27c0da3e8613","resolution":{"observed_at":"2026-08-12T15:44:08.079604Z","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":"2026-08-12T15:44:08.084838Z","title":"Stem-seg: Spatio-temporal em- beddings for instance segmentation in videos","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.084838Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:8c43c4a94d821e5fade88e148797cb7e2a3f291c9fff438b5d99307a5df68294","observation_id":"b0da04a9-edf6-4339-9ba1-2744b246623b","resolution":{"observed_at":"2026-08-12T15:44:08.084838Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15127","last_updated":"2023-11-25T22:28:38Z","snapshot_observed_at":"2026-08-17T12:45:30.627161Z","submitted_at":"2023-11-25T22:28:38Z","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15127","snapshot_observed_at":"2026-08-12T15:44:08.089281Z","title":"Stable video diffusion: Scaling latent video diffusion models to large datasets","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.089281Z"},"links":{"cited_paper":"/paper/2311.15127","citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:c46d89003fa2f8e54f8de0152371d8da75334ddf1b8b6278e283c2474b954281","observation_id":"b3017906-ab9c-4d57-87a3-9f90f9b6e2e1","resolution":{"observed_at":"2026-08-12T15:44:08.089281Z","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":"2026-08-12T15:44:08.094328Z","title":"A thin-plate spline and the decomposition of deformations","venue":null,"work_id":null,"year":1993},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.094328Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:7ca38549d14e97c4cbb4bb15136ebfffbb9a51aaf0cad5d7dc6dfd720b804ea6","observation_id":"fe857f3b-b63f-44c8-b6a5-dff480e3898e","resolution":{"observed_at":"2026-08-12T15:44:08.094328Z","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":"2026-08-12T15:44:09.137975Z","title":"Video generation models as world simulators","venue":null,"work_id":"3c1fa2d6-7b9a-4ae7-9431-7be2f33fc62b","year":2024},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.099228Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:10ccfced5bbb9a7d646b63b1443446e6eab96bca49eb8bd847c223d545e01643","observation_id":"5fc33399-4691-489d-b9a2-baa64f46ecb3","resolution":{"observed_at":"2026-08-12T15:44:09.142723Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.103896Z","title":"Video salient object detection via contrastive features and attention modules","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.103896Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:2227ae0ac7af99e8682c3004aaa2d90f6b43b920b719ad744aea77576bc2ab14","observation_id":"4f25e8ea-10c1-4ca2-9fec-f575aedf37fb","resolution":{"observed_at":"2026-08-12T15:44:08.103896Z","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":"2026-08-12T15:44:08.109083Z","title":"Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.109083Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:c00b0d0d2d528d102e3d29c3af61b98d082546453cc2c0cfcf9186185c2d88aa","observation_id":"40b29569-0028-47ae-8534-dd3de67bdc3c","resolution":{"observed_at":"2026-08-12T15:44:08.109083Z","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":"2026-08-12T15:44:08.113489Z","title":"Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.113489Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:46d5e4ed401b340c6292d008ef5465bc3e1348a1dda4e5ae23ec7a49739da0d8","observation_id":"336dae8f-3bd5-4546-ae8c-5ce038108b17","resolution":{"observed_at":"2026-08-12T15:44:08.113489Z","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":"2026-08-12T15:44:08.117760Z","title":"Global contrast based salient region detection","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.117760Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:8c6910196b5462822152d4ed6068c5175d60e86c65c7582a3d509f1f20abcab5","observation_id":"f29e952b-07c5-42e9-b33a-9148152715da","resolution":{"observed_at":"2026-08-12T15:44:08.117760Z","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":"2026-08-12T15:44:08.122243Z","title":"Tack- ling background distraction in video object segmentation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.122243Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:e0ba269ec24a9bc934a70e4d8b25aa16db7ff2320532f7970d95efd1660f28f4","observation_id":"8b885a3f-80a6-4b49-b099-9d791aae4a92","resolution":{"observed_at":"2026-08-12T15:44:08.122243Z","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":"2026-08-12T15:44:08.126595Z","title":"Treating mo- tion as option to reduce motion dependency in unsupervised video object segmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.126595Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:b5ecb2ab45d2ac88f07221c459d818d27fdf9fcc57c49fc01c75faa322d03d47","observation_id":"a932a8b6-1014-42cd-af8c-7affbe01e5a6","resolution":{"observed_at":"2026-08-12T15:44:08.126595Z","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":"2026-08-12T15:44:09.063311Z","title":"Dual pro- totype attention for unsupervised video object segmentation","venue":null,"work_id":"6f7ccf85-930d-4606-b9ae-f0aac47aad67","year":2024},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.130952Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:caadbddbf616d91d1d031abb3613e10a7b1f7684c6a9c64a0830a6484e07def9","observation_id":"d5800a6f-9a34-46bc-8fc4-76cb8f702f18","resolution":{"observed_at":"2026-08-12T15:44:09.068064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.135412Z","title":"3d u-net: learn- ing dense volumetric segmentation from sparse annota- tion","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.135412Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:82f1ed20fb8f2d499c0e9ca5e4f035e4a637a78297f4c0dfb8e8e91b4630c2fd","observation_id":"3e783403-4183-433b-8412-b594e6a24d0f","resolution":{"observed_at":"2026-08-12T15:44:08.135412Z","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":"2026-08-12T15:44:08.139754Z","title":"The pascal visual object classes (voc) challenge","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.139754Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:990d40a075b4e0f3728be977127db9a5c959127ddf2dfdb7bdd7707a002f9b5f","observation_id":"c572fe00-5bb2-495b-92ba-d0cf9a05c2c2","resolution":{"observed_at":"2026-08-12T15:44:08.139754Z","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":"2026-08-12T15:44:09.027695Z","title":"Structure-measure: A new way to evaluate foreground maps","venue":null,"work_id":"da9fad72-ada9-4e4d-b9ef-0dedf64a8267","year":2017},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.144107Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:e26ad1a657c4b59bd7c425bce5cd99586eef34a163de2dd4d54c8646af361e2e","observation_id":"3d6339c5-ef8a-42cb-ab16-38e28ec13060","resolution":{"observed_at":"2026-08-12T15:44:09.032662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.148481Z","title":"Shifting more attention to video salient object detection","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.148481Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:ab671f44979a0304d90b7b7f3d1544ca3511abd5cb43ec7743e920866dea1404","observation_id":"5663bf56-78eb-400e-8407-efd87eb69842","resolution":{"observed_at":"2026-08-12T15:44:08.148481Z","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":"2026-08-12T15:44:08.152830Z","title":"Bidirectionally learning dense spatio-temporal feature prop- agation network for unsupervised video object segmentation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.152830Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:6c58eeda44954f6c7f0491d1d770da063516cfaa9e16323b260946f503caef58","observation_id":"274a7dfe-9396-4b33-b125-6a8150cbc02c","resolution":{"observed_at":"2026-08-12T15:44:08.152830Z","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":"2026-08-12T15:44:08.157389Z","title":"Temporally efficient gabor transformer for unsu- pervised video object segmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.157389Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:33a2ad25117d0afbe5c7aff2957f3bedc2171e1dd743cd458a9d9ef9b6c2bed9","observation_id":"bb95c596-3757-4674-b5e2-ff6c6d419f57","resolution":{"observed_at":"2026-08-12T15:44:08.157389Z","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":"2026-08-12T15:44:08.161777Z","title":"Pyramid constrained self- attention network for fast video salient object detection","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.161777Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:774ccf1ce09117da7dbd3c312b2d95fdf33dc125ea3170ea0cb3582f0d558fe9","observation_id":"0c4e0e0c-22d9-4b70-9067-722e2668de4c","resolution":{"observed_at":"2026-08-12T15:44:08.161777Z","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":"2026-08-12T15:44:08.971786Z","title":"Sparsectrl: Adding sparse controls to text-to-video diffusion models","venue":null,"work_id":"73d2ae16-efda-4ddd-afd1-c2791a0f29fe","year":2025},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.166276Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:fb40c436485e9a2ac346d87444fb989c39a725b3250c758410db11e9642d2bc4","observation_id":"7b6215f5-3a99-4e22-95e4-0faac167852f","resolution":{"observed_at":"2026-08-12T15:44:08.976566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.170838Z","title":"Semantic contours from inverse detectors","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.170838Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:850111c47e8b6388633d7a5a5a82e0d04382ab6cd1367bcc3cfd86cc26732eee","observation_id":"45352cf1-ca2c-4c09-92c3-3264450d58db","resolution":{"observed_at":"2026-08-12T15:44:08.170838Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.12598","last_updated":"2022-07-26T01:42:07Z","snapshot_observed_at":"2026-08-14T06:37:15.299690Z","submitted_at":"2022-07-26T01:42:07Z","title":"Classifier-Free Diffusion Guidance","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.12598","snapshot_observed_at":"2026-08-12T15:44:08.175594Z","title":"Classifier-free diffusion guidance","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.175594Z"},"links":{"cited_paper":"/paper/2207.12598","citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:517333890c07909a09f99e3984b31cbb84b5dbdd4240ff34b43ddf534fe14475","observation_id":"b2f82f1e-dc0d-437c-8787-15a1dc13b57b","resolution":{"observed_at":"2026-08-12T15:44:08.175594Z","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":"2026-08-12T15:44:08.945292Z","title":"Denoising dif- fusion probabilistic models","venue":null,"work_id":"6fd54dbd-1dab-4960-9e8d-da224f65961f","year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.180489Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:c91569b4fb4878cd57464eddf5b90f2e050381112b399ee1a74d814c2b2e3580","observation_id":"24c001fc-11c1-434c-b179-dbed73c44bdb","resolution":{"observed_at":"2026-08-12T15:44:08.950095Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.930478Z","title":"Full-duplex strategy for video object segmentation","venue":null,"work_id":"80b17975-b314-4a45-ab49-c31af65ef257","year":2021},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.184925Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:2452b0b494daff85b1f43aeaf0437a0a36224f9ecf59f83073c21d6fa162dde2","observation_id":"25bcfe3f-b97a-4d32-8a93-14f27b9d0ed5","resolution":{"observed_at":"2026-08-12T15:44:08.935379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.189325Z","title":"Casnet: A cross-attention siamese net- work for video salient object detection","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.189325Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:d67b61758f0bcb7a2fa23c5ec92641209b9817a1d8662667e7d90558184d028b","observation_id":"37b38d93-7160-45de-955b-b8e634b9810c","resolution":{"observed_at":"2026-08-12T15:44:08.189325Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6114","last_updated":"2022-12-10T21:04:00Z","snapshot_observed_at":"2026-08-14T23:50:45.029465Z","submitted_at":"2013-12-20T20:58:10Z","title":"Auto-Encoding Variational Bayes","version":11},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6114","snapshot_observed_at":"2026-08-12T15:44:08.193845Z","title":"Auto-encoding variational bayes","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.193845Z"},"links":{"cited_paper":"/paper/1312.6114","citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:61d3255075d1b7f37aef01fedf5395dc41a9d1f21e3d66daf68aec3e4c50b952","observation_id":"689577ec-3821-44a1-997e-69c91a99d234","resolution":{"observed_at":"2026-08-12T15:44:08.193845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-12T15:44:08.198686Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.198686Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:9402f7afda3d978ab5d0718e25c246ec2b5e6f2bb94a755febf549392166c38e","observation_id":"30412447-1bbf-44d4-bdfd-07f97dde6158","resolution":{"observed_at":"2026-08-12T15:44:08.198686Z","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":"2026-08-12T15:44:08.904744Z","title":"Pika 1.0, 2023","venue":null,"work_id":"e4ebd097-4af7-48d3-a7e9-c53964765faa","year":2023},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.203410Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:7befd5b9f198a086620af5f74d85541fca283a498a080f9bc180c781138619e5","observation_id":"a7bd2834-1080-4b3c-9c53-e6e4b4dd9a1f","resolution":{"observed_at":"2026-08-12T15:44:08.909900Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.888052Z","title":"Unsupervised video object seg- mentation via prototype memory network","venue":null,"work_id":"2d0af943-83f8-4b0d-bcc3-b53b27fc0b0d","year":2023},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.208191Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:5e9f52b45bb23401a429e73269aa63bb05c3c2b15f67f592c64cee4416b1d7dd","observation_id":"174144dd-921b-403e-bf75-31306c102a49","resolution":{"observed_at":"2026-08-12T15:44:08.893207Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.873266Z","title":"Guided slot attention for unsupervised video object segmentation","venue":null,"work_id":"57d75b12-8a78-4ffb-bb42-7f4a94c2c72d","year":2024},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.212879Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:c48405eeef87b019b7576406198ab3c290425e409ca0f10c940599fd5817d3a9","observation_id":"598f9126-f370-40c1-94cf-1f73e70ffae4","resolution":{"observed_at":"2026-08-12T15:44:08.877986Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.858551Z","title":"Mo- tion guided attention for video salient object detection","venue":null,"work_id":"cb9b79dc-cc87-4dd8-8092-29757da78bc9","year":2019},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.217168Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:10edeb4b5e7cc05f098b1de0be45149649ab025cb6fb4daeea6ba0dfdb5b7986","observation_id":"ae2c48c5-7947-4b7f-a7b2-1aeaf640a1aa","resolution":{"observed_at":"2026-08-12T15:44:08.863295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.842851Z","title":"Movideo: Motion-aware video generation with diffusion model","venue":null,"work_id":"f5f6ccdc-37aa-433e-9cc1-af0a3aaffbd3","year":2025},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.221576Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:a9636b99feda7030a2724724ea4a6502987043a37893e0080e4b562b358df3b5","observation_id":"17d40b90-c8bd-4305-8c6a-ac448ae7b20b","resolution":{"observed_at":"2026-08-12T15:44:08.847657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.11516","last_updated":"2023-09-01T14:02:37Z","snapshot_observed_at":"2026-08-09T16:43:43.047389Z","submitted_at":"2020-08-26T12:24:23Z","title":"Making a Case for 3D Convolutions for Object Segmentation in Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.11516","snapshot_observed_at":"2026-08-12T15:44:08.226138Z","title":"Making a case for 3d convolutions for object segmentation in videos","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.226138Z"},"links":{"cited_paper":"/paper/2008.11516","citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:4a697862d82e9b6bb045e6f090e5c524f6e4eac488ac41b796a947534142bc6f","observation_id":"a395b513-7195-42c5-a617-b41f10002e5b","resolution":{"observed_at":"2026-08-12T15:44:08.226138Z","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":"2026-08-12T15:44:08.827654Z","title":"Segmentation of moving objects by long term video analysis","venue":null,"work_id":"82fc2021-a6d8-4352-9d43-907bd3c033b8","year":2013},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.230801Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:84dcfad6144687f7d07f381e9fc8053c0c1be39a0c22e907859d95dc4f8b86d1","observation_id":"57e33847-88cc-4ade-a4c5-09ed2de78ba3","resolution":{"observed_at":"2026-08-12T15:44:08.832631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.235725Z","title":"Fast video object segmentation by reference- guided mask propagation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.235725Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:e7a170cf4162a463d4c5566e34bfe771b3abbca11e9098cbddf24675f89622b1","observation_id":"63e901eb-f817-4dfb-8b82-8937d5744fc7","resolution":{"observed_at":"2026-08-12T15:44:08.235725Z","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":"2026-08-12T15:44:08.240249Z","title":"Video object segmentation using space-time memory networks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.240249Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:c23eeac63f516957792a73d2a0ef30f5aa606db8ae0bcfd48941b8f8d13603d9","observation_id":"570463cf-fe93-48fb-9f56-ae096e8a5526","resolution":{"observed_at":"2026-08-12T15:44:08.240249Z","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":"2026-08-12T15:44:08.244945Z","title":"Multi-scale interactive network for salient object detection","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.244945Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:692e46b1ba512ef79d72b9747e0a913264b835f14b2cb91e7fe0f71628a222aa","observation_id":"8ab48d67-0e22-4b7f-9905-b7cbda1bbebc","resolution":{"observed_at":"2026-08-12T15:44:08.244945Z","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":"2026-08-12T15:44:08.249525Z","title":"Hierarchical feature align- ment network for unsupervised video object segmentation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.249525Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:2fbaa3ffd8106601c0c208b2077df059baa417114813477517e789d1f7048886","observation_id":"190fa514-586e-4de8-bf12-24641e6a1c1f","resolution":{"observed_at":"2026-08-12T15:44:08.249525Z","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":"2026-08-12T15:44:08.254081Z","title":"A benchmark dataset and evaluation methodology for video object segmentation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.254081Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:67720246cea6a46c7055ff84ff266d8aa3aef27721d2f6f6a21e9c65c3f19a2b","observation_id":"f4756ff3-8954-40f1-ae49-41273e9c5b86","resolution":{"observed_at":"2026-08-12T15:44:08.254081Z","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":"2026-08-12T15:44:08.258637Z","title":"Learning video object segmentation from static images","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.258637Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:78c21959fcca9976ba110c12115cc47f2ce2c3d451739ccf513ebc40917d974e","observation_id":"5b9e1345-bb1c-4d7c-83a1-9e41bc4a6e8a","resolution":{"observed_at":"2026-08-12T15:44:08.258637Z","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":"2026-08-12T15:44:08.753073Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"36f5c6d0-66ac-4ff2-a938-5eb4ee298f14","year":2022},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.263164Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:75b3ca86404819688a4fb5badae21bbba822869f6e188730fe2e3d7373f9b90d","observation_id":"aa0ac10c-112c-46af-bd0f-e1ab43b3d795","resolution":{"observed_at":"2026-08-12T15:44:08.757992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.738392Z","title":"Gen-2, 2023","venue":null,"work_id":"fefe50aa-cea5-474b-a84b-a5569109c0ac","year":2023},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.268153Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:4c3da93d9b8a892c25e7730f61318f55826cb11ed3a9200b9dcec8f8e55684f0","observation_id":"bcbe72b6-30d6-4e7d-be7f-b0379f1e8b54","resolution":{"observed_at":"2026-08-12T15:44:08.743094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.273341Z","title":"Kernelized memory network for video object segmentation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.273341Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:302a924146f6a27bbee63514d5dd67d135751ed7ca8e1aa804a270c2c2b7b8de","observation_id":"5086498e-51de-4c47-953b-4458d10cc76a","resolution":{"observed_at":"2026-08-12T15:44:08.273341Z","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":"2026-08-12T15:44:08.278712Z","title":"Hierarchical mem- ory matching network for video object segmentation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.278712Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:2b8a86919845b72971f72e059ae6c1fc76d5db35253009709311dc18ba7482b2","observation_id":"fea76d9b-ae68-42c5-9ecc-849f223940df","resolution":{"observed_at":"2026-08-12T15:44:08.278712Z","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":"2026-08-12T15:44:08.283301Z","title":"Hierarchical image saliency detection on extended cssd","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.283301Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:d365160bde45f7317b36726f0072bd10bfa04292b04641b5339360d78fb9bbe3","observation_id":"27fa7e9f-f5fd-4dc1-b856-2391c979cb18","resolution":{"observed_at":"2026-08-12T15:44:08.283301Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-08-11T15:38:14.931716Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-12T15:44:08.287761Z","title":"Denoising diffusion implicit models","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.287761Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:fd88490ce3219bcfbd72a92c8a2074b462bc4b48ff6aa7815e9ba2ca9a0fc4e8","observation_id":"71ae7345-d348-4d8a-bd61-de3d354d914f","resolution":{"observed_at":"2026-08-12T15:44:08.287761Z","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":"2026-08-12T15:44:08.694295Z","title":"Improved techniques for training score-based generative models","venue":null,"work_id":"c248c24d-aa1c-4200-922d-d2cf4a768369","year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.292372Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:58c7b46dfb0852e123379e4469bce7381cf4ae209a83c3dfdd2c99f79d8f2fe8","observation_id":"f4acb2a2-6e37-40db-a903-3816120271fa","resolution":{"observed_at":"2026-08-12T15:44:08.699647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.296675Z","title":"Unsupervised video object segmentation with online adversarial self-tuning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.296675Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:69a52ae616cd7b640f4abd454a83de10acdfcdb8f21ecdf031e2ce8bc4280464","observation_id":"4748fe7c-3e8a-45cf-b279-d4a092bd2033","resolution":{"observed_at":"2026-08-12T15:44:08.296675Z","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":"2026-08-12T15:44:08.301378Z","title":"A unified transformer frame- work for group-based segmentation: Co-segmentation, co- saliency detection and video salient object detection","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.301378Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:9793534362b4fb0f2a4d03a02c337c4648006a604efa41e2864017cedc29ccc6","observation_id":"0274b3d3-2d7c-4785-a84a-e83c41232bcc","resolution":{"observed_at":"2026-08-12T15:44:08.301378Z","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":"2026-08-12T15:44:08.305747Z","title":"Raft: Recurrent all-pairs field transforms for optical flow","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.305747Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:845d2ce08e7ef23267d2f1da5cd30091beccc20f74b222becbca225ecd4aa09c","observation_id":"21e8c68d-96c1-4c39-8fea-19e66b4aa5a3","resolution":{"observed_at":"2026-08-12T15:44:08.305747Z","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":"2026-08-12T15:44:08.650895Z","title":"Learning to de- tect salient objects with image-level supervision","venue":null,"work_id":"c706028e-a9d7-4a5f-ad5e-45b05abb6bce","year":2017},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.310249Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:4580e4bfd3d93b32dd54b390557ca0d93fd175745cbc25efa10972d19bdd7727","observation_id":"01564162-d1fe-4309-9630-e282d48662a9","resolution":{"observed_at":"2026-08-12T15:44:08.655777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.634082Z","title":"Consistent video saliency using local gradient flow optimization and global refinement","venue":null,"work_id":"109e0e2f-69e7-467f-95ff-4432f02dd1a1","year":2015},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.314692Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:0fc2cde742e16659cb2231fe6184c584eb46504f60daf58d9ed77996ad09174b","observation_id":"6b861226-6ac5-43e9-a6c6-6e4285c32688","resolution":{"observed_at":"2026-08-12T15:44:08.639271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.319671Z","title":"Video salient object detection via fully convolutional networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.319671Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:3aa97320f1b0639feb8e9bda787cbd855b172f1009f61d2b793838f13c3db914","observation_id":"5e836263-1fd7-4d48-8bbb-fd0b9cde0af8","resolution":{"observed_at":"2026-08-12T15:44:08.319671Z","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":"2026-08-12T15:44:08.323889Z","title":"F3net: fusion, feedback and focus for salient object detection","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.323889Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:4766cba2233f304f4fadb38222c6a4b00294a43363da13d1a18e686ddf10048f","observation_id":"4941c26c-ac96-45c5-ab22-3072e9c8dda0","resolution":{"observed_at":"2026-08-12T15:44:08.323889Z","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":"2026-08-12T15:44:08.328324Z","title":"Cbam: Convolutional block attention module","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.328324Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:d2fad6e0ac745dd677903f1d482d7ef40d9b2dc7b010809e021ec833c9ec2ca2","observation_id":"9cb05069-9ab3-440e-87a2-78c075ca248a","resolution":{"observed_at":"2026-08-12T15:44:08.328324Z","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":"2026-08-12T15:44:08.589305Z","title":"Segformer: Simple and efficient design for semantic segmentation with transform- ers","venue":null,"work_id":"7db1c72b-a656-4a5b-83fc-bb55f5a9181a","year":2021},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.332703Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:0ffa95432a61877a80a1216f6286302c38ae15270b305f2f8af1768f649b7023","observation_id":"170fdbfc-722b-4edd-b4ee-f42585f89283","resolution":{"observed_at":"2026-08-12T15:44:08.594416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.573612Z","title":"Learning motion-appearance co- attention for zero-shot video object segmentation","venue":null,"work_id":"67ec2086-21ae-4926-ab6a-29d6a2757cf5","year":2021},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.337036Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:08aedf877c5af3d231bbd17c3b3b1db425214eb1af8a9bac55f9719e7af8c0c2","observation_id":"eea1c728-d50f-451e-aba0-dfa6060307c5","resolution":{"observed_at":"2026-08-12T15:44:08.578731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:44:08.558299Z","title":"Anchor diffusion for un- supervised video object segmentation","venue":null,"work_id":"3187dffb-7599-413a-ae45-f19ad318e1c8","year":2019},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.341657Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:3ab28741e95aafa16c975a8c19f85dffadfadb358791c324027178e49ee8b060","observation_id":"2193e3aa-2281-4c0e-b438-2124a734a51f","resolution":{"observed_at":"2026-08-12T15:44:08.563339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.08089","last_updated":"2023-08-16T01:43:41Z","snapshot_observed_at":"2026-07-06T16:06:38.424057Z","submitted_at":"2023-08-16T01:43:41Z","title":"DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.08089","snapshot_observed_at":"2026-08-12T15:44:08.346099Z","title":"Dragnuwa: Fine-grained control in video generation by integrating text, image, and trajectory","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.346099Z"},"links":{"cited_paper":"/paper/2308.08089","citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:559e1a6406aa684a7f5c7476a172fae18ba8a5a75a456919c77b9eb157a648b4","observation_id":"a446baea-bd8b-4aec-84f2-336cc30fcbc6","resolution":{"observed_at":"2026-08-12T15:44:08.346099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.04145","last_updated":"2023-11-07T17:16:06Z","snapshot_observed_at":"2026-08-02T12:25:34.488259Z","submitted_at":"2023-11-07T17:16:06Z","title":"I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.04145","snapshot_observed_at":"2026-08-12T15:44:08.350865Z","title":"I2vgen-xl: High-quality image-to-video synthesis via cascaded diffusion models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.350865Z"},"links":{"cited_paper":"/paper/2311.04145","citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:e7120fd7f03546d835ad5f98a75abdac1eda6947c574d9c2b287789d2b92ca94","observation_id":"0fcbb901-1c51-4f91-966c-a4e3bc92121c","resolution":{"observed_at":"2026-08-12T15:44:08.350865Z","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":"2026-08-12T15:44:08.356023Z","title":"Suppress and balance: A simple gated net- work for salient object detection","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.356023Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:5ac94870363ea39f9d42cd9de714218d30f095383d3de06029d4bd5a8b106723","observation_id":"a8bb86d3-c105-4eee-b7f0-a7fe6c1dfe7e","resolution":{"observed_at":"2026-08-12T15:44:08.356023Z","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":"2026-08-12T15:44:08.360567Z","title":"Learning discriminative feature with crf for unsupervised video object segmentation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.360567Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:14bfe72661c62bc4c755e9b6f651d89e63e7dad96ebfd28866a6eb4341d39fcd","observation_id":"4742225a-be60-49a3-95be-a7ddf441308a","resolution":{"observed_at":"2026-08-12T15:44:08.360567Z","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":"2026-08-12T15:44:08.520726Z","title":"Motion-attentive transition for zero-shot video object segmentation","venue":null,"work_id":"926da088-0a98-4ff5-9120-0a251db70c4e","year":2020},"citing_paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-12T15:44:08.365037Z"},"links":{"citing_paper":"/paper/2411.13975"},"observation_digest":"sha256:24aeb08f21335aace8e319c7cda26aeaa7e82c04e9cee83679185d9a315b1a88","observation_id":"1296c2cf-471d-4922-b28e-c68654b94526","resolution":{"observed_at":"2026-08-12T15:44:08.527457Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.13975","last_updated":"2024-11-21T09:41:33Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-15T21:42:40.376001Z","submitted_at":"2024-11-21T09:41:33Z","title":"Transforming Static Images Using Generative Models for Video Salient Object Detection"},"reference_resolution":{"displayed":63,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":42,"verified_exact":0,"verified_fuzzy":21},"total_outbound_references":63},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2411.13975."}