{"as_of":"2026-08-17T03:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:65c4e67ff8e368124d2cb56bd957486db4ecfa3e35c24eac4eea92cfdc289e01","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:51:18.477744Z","state":"measured"},{"denominator":39,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":39,"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/1908.06368/citation-record","integrity":"/paper/1908.06368/integrity","json":"/paper/1908.06368/citation-record.json","paper":"/paper/1908.06368"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:51:19.625865Z","title":"https://deepdrive.berkeley.edu/project/low- latency-deep-inference-self-driving-vehicles","venue":null,"work_id":"7c5248dd-42f2-4f58-adea-5fdff81c2207","year":null},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.201026Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:a858b960a73e1a64de67939bd69840ba19f8d9fd74d6702d6abdc02ca60e2cc2","observation_id":"d4fb9779-9b7c-4d7d-ae72-4a0d0407ee58","resolution":{"observed_at":"2026-08-14T12:51:19.632056Z","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":"2026-08-14T12:51:19.597774Z","title":"Object detection in video with spatiotemporal sampling networks","venue":null,"work_id":"48409126-3a40-4ea3-a685-458361029884","year":2018},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.214260Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:6b6824c855e581b49bee124b095941afbab80a12bc0c098ae2d27e07739ef530","observation_id":"26bd4cd8-7bff-4496-b633-26ba1d979428","resolution":{"observed_at":"2026-08-14T12:51:19.607907Z","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":"2026-08-14T12:51:19.574229Z","title":"Adaptive neural networks for efficient inference","venue":null,"work_id":"3c0d5b3b-ce61-48a2-bbb6-6beed3bcd4ad","year":2017},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.228687Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:0baf66a567566791fa3bf07653c969ebca8c0a95af25e00b9ccbcd2cdc22ec3d","observation_id":"1604b891-7947-4c73-816c-5bb6dff18cb8","resolution":{"observed_at":"2026-08-14T12:51:19.582013Z","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":"2026-08-14T12:51:19.547680Z","title":"Optimizing video object detection via a scale-time lattice","venue":null,"work_id":"47b3b0b8-d9c4-4477-b85d-77708b6ab7ae","year":null},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.236400Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:375a5ae3c8fb9fe84c4802e532367c220a107a1708ac99c3a8792a8a0abf5f19","observation_id":"7285bee3-becc-4f91-a38e-df997954a20d","resolution":{"observed_at":"2026-08-14T12:51:19.553712Z","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":"2026-08-14T12:51:19.522990Z","title":"R-FCN: Object detection via region-based fully convolutional networks","venue":null,"work_id":"3f0ae9fe-47ec-48fb-921a-80ddf114cd0b","year":2016},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.242646Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:7590ff58de1f42d8ad923589d63c853e0d679356ce85065c611322b3a2ede17c","observation_id":"ac81de19-c9ce-428c-9de6-257e94c052a9","resolution":{"observed_at":"2026-08-14T12:51:19.533222Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:51:18.253260Z","title":"ImageNet: A large-scale hierarchical image database","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.253260Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:f22146e942a443dfdc534e2b453ca01f39f19d22638d84a6ac269cacbd408fe6","observation_id":"bb9250fa-8881-46e5-ae67-f7a41033eb20","resolution":{"observed_at":"2026-08-14T12:51:18.253260Z","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":"2026-08-14T12:51:19.479580Z","title":"The pascal visual object classes (VOC) challenge","venue":null,"work_id":"db452cab-89a3-4ef9-86b2-14760708f243","year":2010},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.258594Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:6c048de19447dde6373fd0096292136e5d1435b55e6ac54fa010965f7305ed64","observation_id":"c8cd2d78-7f03-4abf-80fd-e90e27469de1","resolution":{"observed_at":"2026-08-14T12:51:19.487989Z","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":"2026-08-14T12:51:19.451405Z","title":"Detect to track and track to detect","venue":null,"work_id":"0ca5ddf4-cc2e-4a6f-be71-a564adc57974","year":2017},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.264999Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:e1c320d1a994b7635754d797607a83dabfbc5ff23d3f92e5b90f321dc341838b","observation_id":"f006c723-b25f-4535-8353-82d34bcc6fd0","resolution":{"observed_at":"2026-08-14T12:51:19.457109Z","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":"2026-08-14T12:51:19.418395Z","title":"Vision meets robotics: The KITTI dataset","venue":null,"work_id":"99714d34-5f1c-41ee-898d-43a240c01026","year":2013},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.270624Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:9fb3a9b7095ffc32bb78c2f4fc12f4f5577d6af3d307c8caa0a455d2baf3f7ff","observation_id":"26994ec8-d680-4f57-be1a-cb205c565f7f","resolution":{"observed_at":"2026-08-14T12:51:19.424024Z","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":"1712.05896","last_updated":"2017-12-16T02:53:30Z","snapshot_observed_at":"2026-08-14T20:03:06.078421Z","submitted_at":"2017-12-16T02:53:30Z","title":"Impression Network for Video Object Detection","version":1},"cited_work":{"arxiv_id":"1712.05896","doi":null,"metadata_source":"pith","pith_arxiv_id":"1712.05896","snapshot_observed_at":"2026-08-14T12:51:18.691909Z","title":"Impression Network for Video Object Detection","venue":"cs.CV","work_id":"832ff5f1-5f24-4e0b-a45b-8e68aae16e11","year":2017},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.277820Z"},"links":{"cited_paper":"/paper/1712.05896","citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:2abf18b3e9beff80cdacb85451bba19a176e0846bf40b10ff73fc9475d752f7a","observation_id":"07e62fb9-3a60-477d-a1d7-52c523d5f7e7","resolution":{"observed_at":"2026-08-14T12:51:18.707861Z","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":"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":"2026-08-14T12:51:18.285977Z","title":"MobileNets: Efficient con- volutional neural networks for mobile vision applications","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.285977Z"},"links":{"cited_paper":"/paper/1704.04861","citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:a37326031012e21a086f2eaadf96d48229cf97b6f4539e63ce48d25f926ec16a","observation_id":"b3154daf-ca20-44db-a7ff-6cc36de95f33","resolution":{"observed_at":"2026-08-14T12:51:18.285977Z","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":"2026-08-14T12:51:19.393321Z","title":"T-CNN: Tubelets with convolutional neural networks for object detection from videos","venue":null,"work_id":"b5c3e204-e3eb-43a0-9c7e-5b1b49f5030b","year":null},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.298449Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:677cccdd2787d2ea37d9573f0bd836ae96c9161dc4c268069102fb88b7029bbb","observation_id":"06c94e81-6510-41fc-a9d0-7825f201b59c","resolution":{"observed_at":"2026-08-14T12:51:19.399891Z","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":"2026-08-14T12:51:19.358892Z","title":"A discriminative model with multiple temporal scales for action prediction","venue":null,"work_id":"72eade65-25ca-4db2-ae4d-db92127dee7b","year":2014},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.304485Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:2e1c921f87df3a75121b1e849532c25807ef3ff92df76dffdc188091cfeb1fbd","observation_id":"284f985c-06c3-4679-9acb-c3e6ccb36824","resolution":{"observed_at":"2026-08-14T12:51:19.368240Z","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":"1605.07369","last_updated":"2016-05-24T10:40:13Z","snapshot_observed_at":"2026-08-14T21:56:01.429225Z","submitted_at":"2016-05-24T10:40:13Z","title":"Quickest Moving Object Detection","version":1},"cited_work":{"arxiv_id":"1605.07369","doi":null,"metadata_source":"pith","pith_arxiv_id":"1605.07369","snapshot_observed_at":"2026-08-14T12:51:18.628311Z","title":"Quickest Moving Object Detection","venue":"cs.CV","work_id":"c1fc0be4-fd07-4c8b-b190-c055f432da65","year":2016},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.310750Z"},"links":{"cited_paper":"/paper/1605.07369","citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:1d6ef1b724f2c450690ac83e1596981b4a5d6a26cfd717c95a0c72232607d66e","observation_id":"9c305175-169e-4a0d-befb-ae58d84e9cb5","resolution":{"observed_at":"2026-08-14T12:51:18.637135Z","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":"2026-08-14T12:51:19.335548Z","title":"Minimum delay ob- ject detection from video","venue":null,"work_id":"52598b2e-7ad9-4c8c-9dde-f73f148cda22","year":null},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.316539Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:76d006e01ef7f45870ad573226a1ad32c465eb2bb2765a053edb09850474d223","observation_id":"0e0a6355-8d3b-4cc2-913a-dc9e04e0e271","resolution":{"observed_at":"2026-08-14T12:51:19.341775Z","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":"2026-08-14T12:51:19.309355Z","title":"Evaluating real-time anomaly detection algorithms–the numenta anomaly bench- mark","venue":null,"work_id":"1d351e98-f9cf-4584-9dcd-bbf73d24bb06","year":2015},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.321665Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:2fbaa60696497a4835cf9730ceaa7d3ca5fbb40aa876f28d80e10d99ac2e0dbb","observation_id":"3336ee03-43b2-4e36-ad8d-a7c6ee4cce09","resolution":{"observed_at":"2026-08-14T12:51:19.316351Z","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":"2026-08-14T12:51:19.278426Z","title":"The ar- chitectural implications of autonomous driving: Constraints and acceleration","venue":null,"work_id":"719f0661-16e2-4a13-a2ff-de634797a782","year":2018},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.327409Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:cb6f71e46a6782a20df93db6a4be32456995a55bcd09a0e194f65a13113dff82","observation_id":"c20b251b-e95f-4a32-b5ce-6a7b9eacd8c9","resolution":{"observed_at":"2026-08-14T12:51:19.286516Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:51:18.332518Z","title":"Focal loss for dense object detection","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.332518Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:c0e455cf37737f1b3b93367b836f357aab45ce839dfcedfbf143e7af19765d99","observation_id":"2e9ceaa4-ff33-4a79-96c0-1ca93a1f642c","resolution":{"observed_at":"2026-08-14T12:51:18.332518Z","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":"2026-08-14T12:51:19.238369Z","title":"Microsoft CoCo: Common objects in context","venue":null,"work_id":"7b21a711-5a96-4a46-810d-2c71b66cbbfc","year":2014},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.337644Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:e900323669919324caece880cff876437a3a1305ade1e54eb2bebfd351036d13","observation_id":"2c69312b-6c8c-458f-8d2e-546874bae6a6","resolution":{"observed_at":"2026-08-14T12:51:19.245258Z","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":"2026-08-14T12:51:19.212149Z","title":"Mobile video object detec- tion with temporally-aware feature maps","venue":null,"work_id":"ab22c4bc-af8c-4680-a3fb-3692e8265fbc","year":2018},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.342813Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:1900ba417040d15f10cc3c8f0d3011363785e49dd61da75c7fce18d4cdca0999","observation_id":"b748c408-a37b-428b-8440-1277f013c8e4","resolution":{"observed_at":"2026-08-14T12:51:19.220535Z","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":"2026-08-14T12:51:19.185091Z","title":"SSD: Single shot multibox detector","venue":null,"work_id":"755df2e5-e591-4930-a761-1799b0b0f877","year":2016},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.348131Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:897e8460787f26c8968e59163d9d823ad35c34562c0b89adbd09ca1376da0c0f","observation_id":"019aa1bb-fde3-4c75-a67d-894339640cae","resolution":{"observed_at":"2026-08-14T12:51:19.195073Z","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":"2026-08-14T12:51:19.156631Z","title":"Detect or track: Towards cost-effective video object detec- tion/tracking","venue":null,"work_id":"04c4c940-4e85-4090-940b-df5efc50d1c2","year":2019},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.354053Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:abf24d17e36c971e1e25d1390d6bdc5e774a27c0be2b82311c997a5c17e4536b","observation_id":"a66281bd-43d4-4181-aac4-453115c068f8","resolution":{"observed_at":"2026-08-14T12:51:19.167025Z","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":"2026-08-14T12:51:19.128989Z","title":"Learning ac- tivity progression in LSTMs for activity detection and early detection","venue":null,"work_id":"c0214181-10e5-484d-9b74-cdf6b1c9d2a9","year":2016},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.360135Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:767b09267f359ea1697528468f2c988b44fa93da6a1181ef29232c143307dd9c","observation_id":"0e022102-bc8a-4fba-b822-3b26e38418bc","resolution":{"observed_at":"2026-08-14T12:51:19.140830Z","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":"2026-08-14T12:51:19.089623Z","title":"Budget-aware activity detection with a recurrent policy network","venue":null,"work_id":"beb4f070-9951-484b-83e3-5f2a41cc822b","year":2018},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.366496Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:ca0fdc340317d822696ce4231a794a7330bcf3c5171e75a94888b03589083a1f","observation_id":"63c2ee0d-eb65-43f1-aa66-eb632fad07a6","resolution":{"observed_at":"2026-08-14T12:51:19.100493Z","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":"1810.00434","last_updated":"2019-02-19T18:57:18Z","snapshot_observed_at":"2026-08-14T18:21:28.440491Z","submitted_at":"2018-09-30T17:59:42Z","title":"CaTDet: Cascaded Tracked Detector for Efficient Object Detection from Video","version":2},"cited_work":{"arxiv_id":"1810.00434","doi":null,"metadata_source":"pith","pith_arxiv_id":"1810.00434","snapshot_observed_at":"2026-08-14T12:51:18.580967Z","title":"CaTDet: Cascaded Tracked Detector for Efficient Object Detection from Video","venue":"cs.CV","work_id":"c15fa7d1-b726-4276-b76c-8e0265f94956","year":2018},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.377729Z"},"links":{"cited_paper":"/paper/1810.00434","citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:36e225ea11d50a4df518352c40a71a59fb9c23a11244f0e3f54e63b573d826bc","observation_id":"e755f1a4-3b67-4fe3-9ae1-e1f5c4392b63","resolution":{"observed_at":"2026-08-14T12:51:18.599602Z","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":"2026-08-14T12:51:19.061061Z","title":"Towards real-time object detection on embedded systems","venue":null,"work_id":"a6d2ce21-0d50-4c27-a859-a378217618a5","year":2018},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.387957Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:0f704b3300b977296ce139b1f9ec2cea68ede2380f443cf777bbaabbecd692dc","observation_id":"2d3ab68a-f701-4618-846b-593f03bccad8","resolution":{"observed_at":"2026-08-14T12:51:19.069033Z","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":"2026-08-14T12:51:19.028889Z","title":"Moped: A scalable and low latency object recognition and pose estimation system","venue":null,"work_id":"0b3c6d98-90cc-4b33-b9e6-96d210db4672","year":2010},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.397100Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:f221ecdb322bc2f27986712a647c328eea83403c5ce985c91dd0278de15c06ba","observation_id":"c7364cce-b270-4d8b-800c-ec6e7fb3e594","resolution":{"observed_at":"2026-08-14T12:51:19.042894Z","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":"2026-08-14T12:51:18.989467Z","title":"A large- scale benchmark dataset for event recognition in surveillance video","venue":null,"work_id":"59643892-5dfc-4a3c-971c-727c8071ea50","year":2011},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.403494Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:ab8e6ee74f48dd9e3a47c516059083b7c1a4a309c6829cd790f5c8db2f2efa04","observation_id":"2dffad2a-18ad-4e02-b757-b941e4f67047","resolution":{"observed_at":"2026-08-14T12:51:18.997070Z","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":"2026-08-14T12:51:18.962928Z","title":"Quickest detection","venue":null,"work_id":"7e1c63d4-a577-4d98-86cb-f767f56a0313","year":null},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.411046Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:142e02d885715346d447c3a4163ae030ef93d76dd8ed8261aaba3626b808c6df","observation_id":"decca832-e7a2-4ff6-8f7b-1d4a9e041b82","resolution":{"observed_at":"2026-08-14T12:51:18.968218Z","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":"2026-08-14T12:51:18.942976Z","title":"YouTube-BoundingBoxes: A large high-precision human-annotated data set for object detection in video","venue":null,"work_id":"c21ac8d5-0592-4986-8e56-300c3c707b6d","year":2017},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.417952Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:6b64539e71a9f4e9347409a49bc5e22afb2b7547e80a9d55b23d610b84bb54d5","observation_id":"b44889f5-6299-4731-b7c1-637f8d4a04ec","resolution":{"observed_at":"2026-08-14T12:51:18.948410Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:51:18.427923Z","title":"Faster R-CNN: Towards real-time object detection with re- gion proposal networks","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.427923Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:d94c1475144ebab4ce20656acb0bbeb56407d0a5f9ec7337bd9c8d7c5f597694","observation_id":"a790403b-1fae-467c-b39b-08ec77489d53","resolution":{"observed_at":"2026-08-14T12:51:18.427923Z","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":"2026-08-14T12:51:18.902203Z","title":"Encouraging LSTMs to anticipate actions very early","venue":null,"work_id":"31381418-7c7f-4c23-abb8-54e2749eec45","year":2017},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.434581Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:dd66f7a253aada4dedc85e10dde9180734246bba8111addd26b30852080aa393","observation_id":"4d8940d0-d94f-40a4-9c9e-b8079026bf9b","resolution":{"observed_at":"2026-08-14T12:51:18.910519Z","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":"2026-08-14T12:51:18.868341Z","title":"Mul- tilayer and multimodal fusion of deep neural networks for video classification","venue":null,"work_id":"59b90c66-c288-42d7-8900-8931c088f28d","year":2016},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.440298Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:e5e2c7cf6e384025fb30cde2aba192d22d9e4fc694ee356316fbd9cd648cca36","observation_id":"1524b99b-a5c4-4a2a-8314-fe64444c84b4","resolution":{"observed_at":"2026-08-14T12:51:18.883180Z","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":"2026-08-14T12:51:18.845888Z","title":"Making convolutional networks recurrent for visual sequence learn- ing","venue":null,"work_id":"606c2087-f254-44df-8f0d-c7b39afc4cfd","year":2018},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.445874Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:b0937f630cd388ad57656018292b63719594a2147142c61fe6605e3ea0737310","observation_id":"58e5d355-5db9-4859-adcc-6a89b6b1fe46","resolution":{"observed_at":"2026-08-14T12:51:18.852931Z","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":"2026-08-14T12:51:18.822933Z","title":"STEP: Spatio-temporal pro- gressive learning for video action detection","venue":null,"work_id":"f422681a-446a-4cf3-bafc-deb9b36a85fa","year":2019},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.450684Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:427e130996b7c88cc292c4e531fbc4d0263c524fade971c426ea71235498e830","observation_id":"ed256fb9-620c-4bf6-8468-caa82c7b46d4","resolution":{"observed_at":"2026-08-14T12:51:18.832383Z","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":"1805.04687","last_updated":"2020-04-08T09:25:06Z","snapshot_observed_at":"2026-08-14T19:16:08.121001Z","submitted_at":"2018-05-12T09:24:21Z","title":"BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.04687","snapshot_observed_at":"2026-08-14T12:51:18.460593Z","title":"BDD100K: A diverse driving video database with scalable annotation tool- ing","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.460593Z"},"links":{"cited_paper":"/paper/1805.04687","citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:246b0edc61487c51367acff790fe330fe3a5e122d9c8fcd136c21749eff3524a","observation_id":"31aa2bae-64c7-43d8-927d-c6c721eac6d7","resolution":{"observed_at":"2026-08-14T12:51:18.460593Z","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":"2026-08-14T12:51:18.785179Z","title":"ShuffleNet: An extremely efficient convolutional neural net- work for mobile devices","venue":null,"work_id":"319a0c42-60b3-429f-9e6e-a9448fc3a7fd","year":2018},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.466383Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:680bfb8549c2f68c500ed1f8d666014a1b46b19dd868877568d2403264eae8b5","observation_id":"2894fb2b-7d54-4564-9537-df4408e2d649","resolution":{"observed_at":"2026-08-14T12:51:18.796826Z","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":"2026-08-14T12:51:18.758007Z","title":"Flow-guided feature aggregation for video object de- tection","venue":null,"work_id":"92728ffd-f38b-412a-a9b2-b6fa3199c475","year":2017},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.472305Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:9e3ef4e6afc4c0619b8fd83f97259b185879b0a8601e6c5e2e83851e112725af","observation_id":"5191227e-b567-41c9-86f2-ae3de84d5491","resolution":{"observed_at":"2026-08-14T12:51:18.766683Z","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":"2026-08-14T12:51:18.729484Z","title":"Deep feature flow for video recognition","venue":null,"work_id":"26f52502-7c89-4043-bc0c-8a3e44495d3d","year":null},"citing_paper":{"arxiv_id":"1908.06368","last_updated":"2019-11-06T22:50:02Z","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T12:51:18.477744Z"},"links":{"citing_paper":"/paper/1908.06368"},"observation_digest":"sha256:6f6eae29a8b5fb165e1884ed865b98e5b4ad58accc7c2258772e79aba5fae2f6","observation_id":"0477d9b8-4601-43b5-9fc5-6588441b7c1b","resolution":{"observed_at":"2026-08-14T12:51:18.737946Z","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":"1908.06368","last_updated":"2019-11-06T22:50:02Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T18:50:09.438785Z","submitted_at":"2019-08-18T03:36:23Z","title":"A Delay Metric for Video Object Detection: What Average Precision Fails to Tell"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":3,"verified_fuzzy":31},"total_outbound_references":39},"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 17 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:1908.06368."}