{"as_of":"2026-08-16T09:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e2d7ff0d9402f55d5436df18673f5c1fddcfb58ddb9c3ac8b2914cd1c393d223","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":"2026-08-16T06:30:59.297886+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":"2026-08-16T04:44:39.261108Z","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":"sha256:80fd0d7f114259e7154299f3393c538844e1b5f04fe51bb0a937cef938055c8f","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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":"sha256:6070cfd1b8b54f369d3272f05bb7cee882b2289176350e802042f0865ae7a7c4","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1812.08008","last_updated":"2019-05-30T23:46:18Z","snapshot_observed_at":"2026-08-14T17:41:42.294549Z","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":"2026-08-16T04:44:39.261108Z","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:d39e322964758a8b353e6c5e1abc91acf274cc0af9f4a989c6e2a63f33e116a2","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":"2026-08-16T04:44:39.261108Z","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":"sha256:13ce906e957d4a2b6305be3532c79593ca53abaecdc5bb466ea5eee625ec41dd","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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":"sha256:4f5fbf8195324880bd2f3d20ab8989ca5dd353fab956438783509800f63fb17c","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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:a95493211a7829b00aa607d961a041ce3609e09478baa27f0de13612db62fded","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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:e13a96a3bc977af4b0cc40a17f08085e9155280e4fa6c25b9639081eb22801fe","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.02551","last_updated":"2017-08-08T16:32:48Z","snapshot_observed_at":"2026-08-14T20:42:31.690614Z","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":"2026-08-16T04:44:39.261108Z","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":"sha256:87556cc324a7838780a4f24d131f5a89b8760ae0e3c4dd079bc9822e66e6f82c","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":"2026-08-16T04:44:39.261108Z","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:d8c1a6b3132e32fe4a120937ddb784d1e27a97188a0b22185a11c3e2f559f800","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":"2026-08-16T04:44:39.261108Z","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":"sha256:414b92e9dd7b7416bc032052ec4e5ed52ccc3fc115dcaa2f627f2c382f617b3a","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":"2026-07-06T02:11:23.670680Z","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":"2026-08-16T04:44:39.261108Z","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":"sha256:554644668cd5df1e10cebec4765f9784f5c113fc3d94aba3c0e790338706dca2","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":"2026-08-16T04:44:39.261108Z","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:c3d67ec47465c1c18040878cb78c3bd0a40368594f509d71a5e8c26528d30891","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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":"sha256:4849b1181cf340b5bcc461c62cd7f4b3602a1fdcd61fa96d370a123e18be8f31","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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":"sha256:388a2749951df53a24643953ab4fd702e5c18acdf1131039762d9d02aaeae739","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":"2026-08-16T04:44:39.261108Z","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":"sha256:72cd2dc12c34576560a231c4916d2c57958623786d75e85858d9620a53daf92d","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.06031","last_updated":"2018-05-16T12:16:48Z","snapshot_observed_at":"2026-08-14T20:32:07.852905Z","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":"2026-08-16T04:44:39.261108Z","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":"sha256:7bcfdf3a1e1ada9025b743b2d294c6c96ab2bb086445335e8d906696eae821f4","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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":"sha256:9f876f5e6e53d09df16e019935de1e2ff73d9f95043b6ee94ef47f4bcaaee723","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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:cb1e786bfe894e32ab0d9e354d9a164a69c6484c4813dba8892dc5fea1aca527","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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:f50c7cce4a4ed7bf7a3c8ec183d987e27e580313b05d72c475d8cc992ac3d826","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":"2026-08-16T04:44:39.261108Z","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":"sha256:3f1041eb4db8589bbb2a0ca60fd01d42e634ca58cd6cc6242df31ab8e8bb4312","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.09364","last_updated":"2017-08-01T15:18:18Z","snapshot_observed_at":"2026-08-14T20:51:02.257607Z","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":"2026-08-16T04:44:39.261108Z","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":"sha256:694d1030145b8796f105ab628c42f81393ff70b3010e11fc0033c90e395b0289","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":"2026-08-16T04:44:39.261108Z","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:d109815ee228ac0bedc89a8852e10a9d5614225390e85e9f8d6f3e45ec5d3d4e","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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":"sha256:0aaa41c698ccea9a362c4946fc31460b8c564f39b458c7ee49742cb6cfbd7f05","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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":"sha256:52883a8326ce8004d99c964ee2f4f6bac85511c5aa2f930929932909ea89efd8","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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":"sha256:3bafa9c780367443b405d551b73657530cc1fcde03708d92e9da7ea12490be2c","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 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-16T04:44:39.261108Z","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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:1908.06692."}