{"as_of":"2026-08-14T07:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2fb115988a9e2dacb1fccbc07957fde599952d1dba7b11230c144450fe3ecdcf","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T18:32:49.477438Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+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/2501.11288/citation-record","integrity":"/paper/2501.11288/integrity","json":"/paper/2501.11288/citation-record.json","paper":"/paper/2501.11288"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T18:32:50.185004Z","title":"Exploring simple 3d multi-object tracking for autonomous driving,","venue":null,"work_id":"6b2b621a-62d2-44e5-831e-8c80059ddf8d","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.252852Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:18c96759a8f10224eea07d677ab86ad38a06975d511ce2e0c1a06892e448b93a","observation_id":"2f4bc0ac-d69f-4452-a081-3a320c82cd3c","resolution":{"observed_at":"2026-08-10T18:32:50.188442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.174874Z","title":"Multi-object tracking co- processor for multi-channel embedded dvr systems,","venue":null,"work_id":"70854658-a5a2-4bb6-a8ca-a6e8e55a8bdd","year":2012},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.257590Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:82e15695a220da860de2cdc78da32f0497fc1b2f05e1fc9023851d139a23cac6","observation_id":"cb074ba8-9d32-47f0-896d-8675ca7a9a2b","resolution":{"observed_at":"2026-08-10T18:32:50.178633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.164305Z","title":"A novel tracking algorithm using thermal and optical cameras fused with mmwave radar sensor data,","venue":null,"work_id":"21a2a91c-23d2-4386-9306-e752e1c259b9","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.261388Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:ab0777abdcc27277377b4c695947191aa89557c46606d43302c2817316598060","observation_id":"986ac092-beb9-4f25-9efe-4205995ade7b","resolution":{"observed_at":"2026-08-10T18:32:50.168345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.154133Z","title":"Bandt: A border-aware network with deformable transformers for visual tracking,","venue":null,"work_id":"5a5f2b90-6666-4e83-8e1c-64543b1441cc","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.265195Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:00252ebb895458735f43b1c9850ee44251e9a87e66bf2107d1e8a86197f82e8f","observation_id":"4727f3ea-e14c-48c3-9473-b83eec3fbf2c","resolution":{"observed_at":"2026-08-10T18:32:50.157553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.144233Z","title":"Human video instance segmen- tation and tracking via data association and single-stage detector,","venue":null,"work_id":"bae9b1bb-ed90-483a-8536-70df6aa13a8c","year":2024},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.269109Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:bffd9a4aa6c6d2423119e83ca6dcdaef7d24d9a2b07031d1102a86cc24992528","observation_id":"5042e99c-057f-4ef0-a575-5244d2bc687f","resolution":{"observed_at":"2026-08-10T18:32:50.147595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.134054Z","title":"Simple online and realtime tracking,","venue":null,"work_id":"e6744396-ee49-4a94-82ed-01d79f17477b","year":2016},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.273072Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:48182e11a3697c8286225517499749c9d550720169ebdf30bd6d08540ce8e9be","observation_id":"2152162e-76b4-4900-afa9-d6716076ba85","resolution":{"observed_at":"2026-08-10T18:32:50.137481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.123605Z","title":"High-speed tracking-by- detection without using image information,","venue":null,"work_id":"2f51c165-7199-4e36-95f9-18aa320918d1","year":2017},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.277111Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:c7f5865a7cbd68a2b0d6f10263b91f675941cb20e2eb758ca0f6f9a553ec2f78","observation_id":"963c6537-5f1a-4ec4-ac06-c269e5caa36f","resolution":{"observed_at":"2026-08-10T18:32:50.127423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.111246Z","title":"Simple online and realtime tracking with a deep association metric,","venue":null,"work_id":"26397674-1ddb-471a-8167-94fbb9879e30","year":2017},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.280803Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:e95c574159d74f1862182b6beefde85df5bbc1d4ad80bc021742704efd2abf6c","observation_id":"5ef82084-1c7b-4921-8f81-d7c58832cd86","resolution":{"observed_at":"2026-08-10T18:32:50.115542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.099294Z","title":"Bytetrack: Multi-object tracking by associating every detection box,","venue":null,"work_id":"8645b8f4-26ad-4d0b-affd-87f86154bd06","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.284338Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:7952707bb621642553892c95d47484418f2002ecb8cbe1bef1c942090efb1e06","observation_id":"9d129605-b524-43eb-a54d-0462c18ada72","resolution":{"observed_at":"2026-08-10T18:32:50.103151Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.087830Z","title":"Observation- centric sort: Rethinking sort for robust multi-object tracking,","venue":null,"work_id":"10182e63-8a04-4620-a0a3-9fed2c509528","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.288040Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:196624420c9712087230f24a44e737490219f248f198355c5ece263f240399f5","observation_id":"56531aae-b233-4d4d-9f86-5f07d5745c98","resolution":{"observed_at":"2026-08-10T18:32:50.091883Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.076264Z","title":"Faster r-cnn: Towards real-time object detection with region proposal networks,","venue":null,"work_id":"cc906751-8f2e-4744-af3d-cab15f17256a","year":2015},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.291729Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:5324ef195e070b066ace6f2042f035431b4fc9435d4405e1dbc59c242fc0c369","observation_id":"9e31e5b7-f08f-436e-b8fd-002a81b3d454","resolution":{"observed_at":"2026-08-10T18:32:50.080574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.08430","last_updated":"2021-08-06T03:22:14Z","snapshot_observed_at":"2026-07-06T11:30:06.143581Z","submitted_at":"2021-07-18T12:55:11Z","title":"YOLOX: Exceeding YOLO Series in 2021","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.08430","snapshot_observed_at":"2026-08-10T18:32:49.295283Z","title":"Yolox: Exceeding yolo series in 2021,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.295283Z"},"links":{"cited_paper":"/paper/2107.08430","citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:eac6b9d3d73a97bcfce988689871c32f470bc42a93009cced670ba972b08d1c6","observation_id":"5ac841b8-13d2-4005-a172-4f429bf5cea9","resolution":{"observed_at":"2026-08-10T18:32:49.295283Z","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":"2026-08-10T18:32:50.065097Z","title":"On implementing 2d rectangular assignment algorithms,","venue":null,"work_id":"89bb5c17-f5aa-47ba-82fb-ac2236731931","year":2016},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.299416Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:160f233189266b4e24f58745b89988c6608915e5140b75efc9648a0804fcea2d","observation_id":"92b2b437-c845-429a-ae67-aa615ba8cd2d","resolution":{"observed_at":"2026-08-10T18:32:50.068914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:50.053463Z","title":"Dancetrack: Multi-object tracking in uniform appearance and diverse motion,","venue":null,"work_id":"835ba558-d2b6-4abe-b71a-7e0c316ebd87","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.303086Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:16f45f8d00b9d71e2edc6b8a9aba32a763be3f149a9b2b81b53c33a07ffd15dc","observation_id":"53a4f87a-fd54-498c-a9f2-2233e4d23610","resolution":{"observed_at":"2026-08-10T18:32:50.057544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05238","last_updated":"2023-11-20T06:57:05Z","snapshot_observed_at":"2026-08-13T11:21:03.707278Z","submitted_at":"2023-06-08T14:36:10Z","title":"SparseTrack: Multi-Object Tracking by Performing Scene Decomposition based on Pseudo-Depth","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05238","snapshot_observed_at":"2026-08-10T18:32:49.306619Z","title":"Sparsetrack: Multi- object tracking by performing scene decomposition based on pseudo- depth,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.306619Z"},"links":{"cited_paper":"/paper/2306.05238","citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:b95910330424c0feb5f497a590ca8750e6ac471a5064ad8dad6f541a2bef9040","observation_id":"bc1d58a4-619e-4a46-9583-a7fb9502a81c","resolution":{"observed_at":"2026-08-10T18:32:49.306619Z","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":"2026-08-10T18:32:49.310590Z","title":"Contributions to the theory of optimal control,","venue":null,"work_id":null,"year":1960},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.310590Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:f0b01c982a701ed329509367a452da25f7aece42b2f4d92bdac6e1cfcce2f365","observation_id":"12517307-0a55-44b4-a08b-c32bdc76495e","resolution":{"observed_at":"2026-08-10T18:32:49.310590Z","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":"2026-08-10T18:32:49.313811Z","title":"Generalized intersection over union: A metric and a loss for bound- ing box regression,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.313811Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:12f5debc032d9c333cfc74d87df2858efea6434dbfa97a7d2323c618a2cc5bf6","observation_id":"b56833b0-58ff-4af6-bf83-cecb21397c52","resolution":{"observed_at":"2026-08-10T18:32:49.313811Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.14651","last_updated":"2022-07-07T15:36:49Z","snapshot_observed_at":"2026-08-13T15:14:12.197118Z","submitted_at":"2022-06-29T13:45:03Z","title":"BoT-SORT: Robust Associations Multi-Pedestrian Tracking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.14651","snapshot_observed_at":"2026-08-10T18:32:49.316820Z","title":"Bot-sort: Robust associa- tions multi-pedestrian tracking,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.316820Z"},"links":{"cited_paper":"/paper/2206.14651","citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:494d4c1714e4601850301a3343b7b517acbbd4df6a10a78fc88f30febc62965f","observation_id":"68dd3b1c-7c6c-4bd0-a3f6-49981f657a01","resolution":{"observed_at":"2026-08-10T18:32:49.316820Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.15460","last_updated":"2021-05-04T15:58:37Z","snapshot_observed_at":"2026-07-06T10:28:58.102232Z","submitted_at":"2020-12-31T06:03:00Z","title":"TransTrack: Multiple Object Tracking with Transformer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.15460","snapshot_observed_at":"2026-08-10T18:32:49.320273Z","title":"Transtrack: Multiple object tracking with transformer,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.320273Z"},"links":{"cited_paper":"/paper/2012.15460","citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:1a03388d6205b8e8e6d9ac18dc94e294087b36a2a8b104b5310bbabbb20f7a89","observation_id":"c8a7bca3-122e-41f1-a467-ced17da35483","resolution":{"observed_at":"2026-08-10T18:32:49.320273Z","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":"2026-08-10T18:32:50.028159Z","title":"Track- former: Multi-object tracking with transformers,","venue":null,"work_id":"2c7c1122-bc7f-4d1f-b269-28c1a61906f1","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.324032Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:9e551ad1842e948c6ad99aeb71bd153bbb74050c7415ebe26936ac8c69ba22ea","observation_id":"1636d5db-7d2b-4382-8f87-bdf889df6621","resolution":{"observed_at":"2026-08-10T18:32:50.032219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.327753Z","title":"Motr: End-to-end multiple-object tracking with transformer,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.327753Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:d73bcae1b3d0ae09bbeda0c797e1d3dd3866be0541db744449cb9fe3f25ad368","observation_id":"599362e5-d332-4bdd-bb94-db7dc069a251","resolution":{"observed_at":"2026-08-10T18:32:49.327753Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.02767","last_updated":"2018-04-08T22:27:57Z","snapshot_observed_at":"2026-08-06T11:09:16.409556Z","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":"2026-08-10T18:32:49.331294Z","title":"Yolov3: An incremental improvement,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.331294Z"},"links":{"cited_paper":"/paper/1804.02767","citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:5e173c0f63823f9893408af8ab2013d73ebd4e00df4cce392f5a8a917c974a22","observation_id":"38ef0d4b-536a-4e4a-8aa0-65ed0d7b1ea9","resolution":{"observed_at":"2026-08-10T18:32:49.331294Z","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":"2026-08-10T18:32:50.009861Z","title":"Learnable graph matching: Incorporating graph partitioning with deep feature learning for multi- ple object tracking,","venue":null,"work_id":"42b71ddc-021a-4354-8fe3-8aec7af52b5a","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.335516Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:a7f5c91c82c331022777f6def55b02e620c2d9c71661b1a59500545cb53de20e","observation_id":"b5b68080-df31-45c2-8ce2-ebbed3e81dc6","resolution":{"observed_at":"2026-08-10T18:32:50.014037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.339512Z","title":"The hungarian method for the assignment problem,","venue":null,"work_id":null,"year":1955},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.339512Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:a3007454795bc0900b6f6ffd3d8e03838d078754a8890e88b26cc57057585f24","observation_id":"525a62e4-2ee5-4fce-9d00-6094557b90bd","resolution":{"observed_at":"2026-08-10T18:32:49.339512Z","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":"2026-08-10T18:32:49.992349Z","title":"Similarity based person re- identification for multi-object tracking using deep siamese network,","venue":null,"work_id":"2f7f2045-17ab-4636-b328-41a346515869","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.343495Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:88dce25fd7b7f048a67fe699e069ac3302c924b6f803ba927d6f2f582a5a992e","observation_id":"7d5cd847-b3d9-46bd-981d-c04ca0ad9396","resolution":{"observed_at":"2026-08-10T18:32:49.996127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.981871Z","title":"A strong baseline and batch normalization neck for deep person re-identification,","venue":null,"work_id":"7e1921f9-c9ec-4431-b58f-189a75a59bf0","year":2020},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.347169Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:f388c2241d13ee78fed9910c606f9e41ad5cb90a88e8054cc55e85c687296530","observation_id":"38bec119-c525-4853-8ac1-65db1f79ceed","resolution":{"observed_at":"2026-08-10T18:32:49.985669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.970957Z","title":"Fastreid: A pytorch toolbox for general instance re-identification,","venue":null,"work_id":"35152943-ca7b-4ab8-9d75-94dd6831b26b","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.351047Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:e653cff581bd34d75deec870c560257cb35f0c425ced507876851161f93cb33c","observation_id":"ad90b6c1-affa-49e3-9a05-82579ac41eb4","resolution":{"observed_at":"2026-08-10T18:32:49.974650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.961750Z","title":"Towards real-time multi-object tracking,","venue":null,"work_id":"74482e1a-1fbc-4cb1-bf97-a90aafd039ea","year":2020},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.354828Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:1d475fa494e4d28cc7cc7072e3a97c304078f76cb31470fdf8ff49867d057d48","observation_id":"504ec9ba-3c04-4a22-aa79-23ce7b1e8796","resolution":{"observed_at":"2026-08-10T18:32:49.965022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.951868Z","title":"Fairmot: On the fairness of detection and re-identification in multiple object tracking,","venue":null,"work_id":"ffd05ed9-db65-442f-a19f-50decc8ec535","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.358891Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:199dea47783b080cc4eebbddf302cd34805f2e5fd12585b027fdb002ea592d87","observation_id":"798c1b87-d771-4805-9394-77affea790f7","resolution":{"observed_at":"2026-08-10T18:32:49.955173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.941875Z","title":"Strong- sort: Make deepsort great again,","venue":null,"work_id":"c3fece72-591a-4a5b-8363-0e66800fe6bf","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.362729Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:88887e8d28dfd8117ef113753dc9e9001e509b46844d4a4bfb0f6a9ea42abbbb","observation_id":"946b1d5d-c5e1-4688-83e3-7b6768294acb","resolution":{"observed_at":"2026-08-10T18:32:49.945199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.930606Z","title":"Stat: Multi-object tracking based on spatio-temporal topological constraints,","venue":null,"work_id":"99a2cfe3-5880-4e05-84ed-c982051169dc","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.366537Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:73b7ddeda668a35f7f9d4c5813cbd293cae1532f7f84ff86dadb8e1d351106f0","observation_id":"c7861be9-2375-4e26-8a6a-379acc3b9f07","resolution":{"observed_at":"2026-08-10T18:32:49.934745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.918403Z","title":"Fast re-obj: Real-time object re- identification in rigid scenes,","venue":null,"work_id":"ef042b1b-1ae9-4d91-8d72-2b4a2d97b2a2","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.370454Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:115b126b8a31c96317a63dca984f7d9641af6928f95f302e580d8198f667e373","observation_id":"5a0940e4-07bf-486f-a390-a910f2ec65f2","resolution":{"observed_at":"2026-08-10T18:32:49.922785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.08063","last_updated":"2020-08-18T17:45:56Z","snapshot_observed_at":"2026-08-09T15:51:01.577993Z","submitted_at":"2020-08-18T17:45:56Z","title":"AB3DMOT: A Baseline for 3D Multi-Object Tracking and New Evaluation Metrics","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.08063","snapshot_observed_at":"2026-08-10T18:32:49.374389Z","title":"Ab3dmot: A baseline for 3d multi-object tracking and new evaluation metrics,","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.374389Z"},"links":{"cited_paper":"/paper/2008.08063","citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:4bf987983e8ffafe2d93f42c9da3f4a55d063189c10657b023b8d45d71e6451c","observation_id":"71b157a2-f310-4491-9e79-54d7e9b73e53","resolution":{"observed_at":"2026-08-10T18:32:49.374389Z","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":"2026-08-10T18:32:49.906388Z","title":"Center-based 3d object detection and tracking,","venue":null,"work_id":"bd97770e-64e8-467c-981d-2fedb7eb9e8d","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.378591Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:42fbf538d1f5d0036efc264d7c2a6c85955c259650a9ab89a59b2a273af17a98","observation_id":"1f6f4fe9-69d7-4e0a-833e-5692ccb818dc","resolution":{"observed_at":"2026-08-10T18:32:49.910559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.894384Z","title":"Eagermot: 3d multi-object tracking via sensor fusion,","venue":null,"work_id":"79e242ca-fd1e-4bdc-865e-b9104642613e","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.382507Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:5509db7c3f3a6a3227a5a5346cb5143f79884a1179bcb626ee6833371331f17a","observation_id":"0a2a95a7-4f6d-4dbc-8a21-74668affc6f3","resolution":{"observed_at":"2026-08-10T18:32:49.898674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.882633Z","title":"Quo vadis: Is trajectory forecasting the key towards long-term multi-object track- ing?","venue":null,"work_id":"deab84ea-523d-4b81-b749-45faa3885f7c","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.386324Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:340e5ec934a4aa5c69584d325a5884986caa12712f96cfebfd3385901edd549c","observation_id":"c10cc2d1-2f6a-41a7-845d-e6eb3123d064","resolution":{"observed_at":"2026-08-10T18:32:49.886529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.870508Z","title":"Depth perspective-aware multiple object tracking,","venue":null,"work_id":"12fc3d1f-e5b9-4aa8-9a66-f70ce3c27142","year":2024},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.390403Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:96dd0aa274403d8fb50330dde9a1a1ffa5dcee40132a3647fc183d80d8292c45","observation_id":"9d1545b0-cc97-4e8b-937f-3a9db5b544a5","resolution":{"observed_at":"2026-08-10T18:32:49.874671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.857418Z","title":"The opencv library","venue":null,"work_id":"3baaca8d-72f2-4492-992e-98192bd7decf","year":2000},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.394343Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:8753bbb45c1a9f87147dd983344f009998c42ab5ed74b9aaed7a059a8938e266","observation_id":"f5e4b6a7-16a0-4b97-9879-927ef10ea522","resolution":{"observed_at":"2026-08-10T18:32:49.862094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.844171Z","title":"Good features to track,","venue":null,"work_id":"a50b1f48-de3f-487c-953a-802dc37a4fcd","year":1994},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.398366Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:48abdcf7bd158a8b97c6d5382c695e7cb0288a1a77591edc6149acfb43c28aa2","observation_id":"a41025ef-5eeb-4bb2-8e85-be56e773a565","resolution":{"observed_at":"2026-08-10T18:32:49.848887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.830665Z","title":"Pyramidal implementation of the affine lucas kanade feature tracker description of the algorithm,","venue":null,"work_id":"41ce46dd-7017-45d9-bff7-4a742d5ba0d0","year":2001},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.402300Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:300848f80b9b99809b3576025b23b7fca753012144c28c85c3fa22a050a470fb","observation_id":"9cc9ebb0-9034-40c2-b00d-c0a18d553610","resolution":{"observed_at":"2026-08-10T18:32:49.835408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.406038Z","title":"Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,","venue":null,"work_id":null,"year":1981},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.406038Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:14f6edd053755fdea4b76a70c58f786b982be825da365709f19091da702a21cd","observation_id":"53bbbba3-f4af-4f6b-863a-662107f90d28","resolution":{"observed_at":"2026-08-10T18:32:49.406038Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1603.00831","last_updated":"2016-05-03T23:55:38Z","snapshot_observed_at":"2026-08-03T05:59:06.882015Z","submitted_at":"2016-03-02T19:07:56Z","title":"MOT16: A Benchmark for Multi-Object Tracking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1603.00831","snapshot_observed_at":"2026-08-10T18:32:49.409892Z","title":"Mot16: A benchmark for multi-object tracking,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.409892Z"},"links":{"cited_paper":"/paper/1603.00831","citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:81e78a4fd812f69bf3606a831b827148bb123288398939e38470eb347df35fff","observation_id":"22d3ab99-6307-4d1e-a38c-18da21a90ab2","resolution":{"observed_at":"2026-08-10T18:32:49.409892Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.09003","last_updated":"2020-03-19T20:08:24Z","snapshot_observed_at":"2026-08-10T18:10:19.092488Z","submitted_at":"2020-03-19T20:08:24Z","title":"MOT20: A benchmark for multi object tracking in crowded scenes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.09003","snapshot_observed_at":"2026-08-10T18:32:49.413488Z","title":"Mot20: A bench- mark for multi object tracking in crowded scenes,","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.413488Z"},"links":{"cited_paper":"/paper/2003.09003","citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:a7a2bbab631916e36bcf6e22d9493b8e7e160191724d714bfa394ea7d4f493bc","observation_id":"fcef04ff-6299-4e55-8441-479a416bb16a","resolution":{"observed_at":"2026-08-10T18:32:49.413488Z","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":"2026-08-10T18:32:49.809746Z","title":"Hota: A higher order metric for evaluating multi-object tracking,","venue":null,"work_id":"68e4d640-43c6-419f-82e8-377894b46f2d","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.417180Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:fd0cbc09a1d612faebf862f8bedf424ed61b288b2ee8ad76b487ce44b6c3d039","observation_id":"7743903b-3f68-4857-abc3-af4bf6d58ebb","resolution":{"observed_at":"2026-08-10T18:32:49.813561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.798928Z","title":"Evaluating multiple object tracking performance: the clear mot metrics,","venue":null,"work_id":"49be3e19-1c46-4f42-9599-dc5f6f095609","year":2008},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.420732Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:a71bca87cbd251c0b82de87c059903b81639fa49fa54c44794766f10844dcdba","observation_id":"ae84758e-dec6-49af-8303-ee1d0806db01","resolution":{"observed_at":"2026-08-10T18:32:49.802404Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.788020Z","title":"Performance measures and a data set for multi-target, multi-camera tracking,","venue":null,"work_id":"6684ed34-b82d-4fef-80c6-d8bb13ebe1fb","year":2016},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.424009Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:358fd30a615c0c8bba775011cf8f3cc802f4219d1a689cc2a81e6378c1e5c8f7","observation_id":"1e53f403-2f79-4f05-bf72-c369b12eacaf","resolution":{"observed_at":"2026-08-10T18:32:49.791559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.776401Z","title":"Track to detect and segment: An online multi-object tracker,","venue":null,"work_id":"141e4a52-a80a-46f2-9c81-21ad7f311072","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.427324Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:ed846b4ac9a451ab4f9c94cbe60f99bcf7156390fcfcdf80280713d1e3391e89","observation_id":"f62649a6-4a00-421c-a559-85278ba56983","resolution":{"observed_at":"2026-08-10T18:32:49.780405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.765230Z","title":"Global tracking transformers,","venue":null,"work_id":"95973e67-6b51-46c3-9ce1-db2ef9d90021","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.430696Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:dcdaaaef8629ac11e4ad6f41610f1c776e84418c84aad941b2244be0e0b30bb1","observation_id":"4ef2531e-80aa-42ec-a5b6-b4b930a51eeb","resolution":{"observed_at":"2026-08-10T18:32:49.769035Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.753232Z","title":"Tracking objects as points,","venue":null,"work_id":"45d06017-cabb-48c6-8a68-eb5338e7dc31","year":2020},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.434592Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:e0c5d8094e76623c7940ba86488175e233f59e8a9cd9507c57445eac44402bb3","observation_id":"279402e4-5864-413e-b967-d84857743b19","resolution":{"observed_at":"2026-08-10T18:32:49.757226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.741019Z","title":"Quasi- dense similarity learning for multiple object tracking,","venue":null,"work_id":"d752a631-afb3-46a3-b172-f724139f87f4","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.438682Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:93ac454d9ee17e5052f8d1a7bcb48b15481f6d4d6ac030b35449803701af1be2","observation_id":"afd77e0a-c0e6-45be-b737-98123e742d35","resolution":{"observed_at":"2026-08-10T18:32:49.745324Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.728547Z","title":"Memot: Multi-object tracking with memory,","venue":null,"work_id":"0fa53657-fac5-4f22-b7be-004d9ed66ac8","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.442356Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:2a17e2a6a1ad753e6068be2eab1ecb7871f2e7a121c9e74edd3d1a7ced56f0e3","observation_id":"72493d52-05f3-4c52-a248-9c415594535f","resolution":{"observed_at":"2026-08-10T18:32:49.732880Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.715135Z","title":"Motfr: Multiple object tracking based on feature recoding,","venue":null,"work_id":"046fdbb0-787d-4207-b914-3b2688dd57bf","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.446180Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:9ae08bd4672e62570d91036797eaddaf835cd7a6103710b96a60d03ae1b9a33e","observation_id":"97116499-cfa8-4424-bf54-ebdc90bae7e7","resolution":{"observed_at":"2026-08-10T18:32:49.719577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.701917Z","title":"Modelling ambiguous assignments for multi- person tracking in crowds,","venue":null,"work_id":"6c89cf26-1fde-4f23-a4b9-2ca065232f4e","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.450132Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:cf5f779a8760b33df7c1d95d10cd1755c8991f22f85cb6415eab9a6cfff42faa","observation_id":"351cbb3f-708a-4e47-9e7a-c59009964356","resolution":{"observed_at":"2026-08-10T18:32:49.706209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.688399Z","title":"Motrv2: Bootstrapping end-to-end multi-object tracking by pretrained object detectors,","venue":null,"work_id":"fdce1a33-05b9-4f35-9237-0b7d8e811c9b","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.454167Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:d8609e5b812f7a6b025fec039c8b75618b2c47f1a8d808bd069ad1341383cf3e","observation_id":"4d5bb78d-bf13-4fa1-a4e2-a3fffbcac1ad","resolution":{"observed_at":"2026-08-10T18:32:49.692650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.673794Z","title":"Looking beyond two frames: End-to-end multi-object tracking using spatial and temporal transformers,","venue":null,"work_id":"a515409e-10f2-43e3-bea1-c1dc45debac3","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.458414Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:e38042e2be9dbd40d18efe2bad2e19657cd19148d3ec394b9319da20f503bb42","observation_id":"a45a9027-d001-4212-8566-773601103263","resolution":{"observed_at":"2026-08-10T18:32:49.678520Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.660920Z","title":"Multiple object tracking with correlation learning,","venue":null,"work_id":"845c9b22-3c01-44a4-89e4-95e0b27c8e31","year":2021},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.462355Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:3dc7934cc01fab0eeade15e2a902ed86150dbd7723685d396fe8ceee5773afd8","observation_id":"4c9b45ae-2fbb-4e7a-8600-667f03472bb1","resolution":{"observed_at":"2026-08-10T18:32:49.665097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.648428Z","title":"Transmot: Spatial- temporal graph transformer for multiple object tracking,","venue":null,"work_id":"b1e19a00-c30b-4857-b0d5-23de07e7811d","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.466154Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:c4bf20d8138c9bc43495a7525cbfe826ebdb300faa16ef67c7a9ebff41f25d9b","observation_id":"78d8b582-f377-4432-b330-491d8ece47c3","resolution":{"observed_at":"2026-08-10T18:32:49.652517Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.635763Z","title":"Relationtrack: Relation-aware mul- tiple object tracking with decoupled representation,","venue":null,"work_id":"80983510-5387-4eaf-916c-f80a8c7bc3d7","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.469910Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:f2dd8e360c1b9a10f301c4ceddaa61f933c5fb9f108e5209e48e047cae4c0d7b","observation_id":"2ccbb19d-9fa0-4319-9732-36c61cee2872","resolution":{"observed_at":"2026-08-10T18:32:49.639742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.623251Z","title":"Rethinking the competition between detection and reid in multiobject tracking,","venue":null,"work_id":"17e92f9f-a0a9-413c-ae51-55e3fbb94d03","year":2022},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.473769Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:499c9e060f7b483928310846ab4ee3e3bc1836281d7c6112cd1c93bb89d141be","observation_id":"6921ba04-cb8d-4400-9cb5-7a080f00ae7d","resolution":{"observed_at":"2026-08-10T18:32:49.627372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T18:32:49.608598Z","title":"Simple cues lead to a strong multi-object tracker,","venue":null,"work_id":"039c9ac0-6fd2-4fc6-941a-7024264e679e","year":2023},"citing_paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-10T18:32:49.477438Z"},"links":{"citing_paper":"/paper/2501.11288"},"observation_digest":"sha256:78be3cfb0c5b94581ae3aeba383f1c8016584d174354dec91fa806a5ab3f3c5c","observation_id":"b3464a4c-bad4-49e2-8fba-f301d0943a10","resolution":{"observed_at":"2026-08-10T18:32:49.614412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.11288","last_updated":"2025-01-20T05:50:39Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T21:25:10.564751Z","submitted_at":"2025-01-20T05:50:39Z","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":13,"verified_exact":0,"verified_fuzzy":47},"total_outbound_references":60},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2501.11288."}