{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:K63RN52QKOWXHATYNZIWNYZFJP","short_pith_number":"pith:K63RN52Q","schema_version":"1.0","canonical_sha256":"57b716f75053ad7382786e5166e3254be04f9fbec2c34e070e38bc385b960c13","source":{"kind":"arxiv","id":"2407.10151","version":2},"attestation_state":"computed","paper":{"title":"Lost and Found: Overcoming Detector Failures in Online Multi-Object Tracking","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Lorenzo Vaquero, Manuel Mucientes, Victor M. Brea, Xavier Alameda-Pineda, Yihong Xu","submitted_at":"2024-07-14T10:45:12Z","abstract_excerpt":"Multi-object tracking (MOT) endeavors to precisely estimate the positions and identities of multiple objects over time. The prevailing approach, tracking-by-detection (TbD), first detects objects and then links detections, resulting in a simple yet effective method. However, contemporary detectors may occasionally miss some objects in certain frames, causing trackers to cease tracking prematurely. To tackle this issue, we propose BUSCA, meaning `to search', a versatile framework compatible with any online TbD system, enhancing its ability to persistently track those objects missed by the detec"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2407.10151","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-14T10:45:12Z","cross_cats_sorted":[],"title_canon_sha256":"13244729e286ff8dd3ccaffc81053565892e2ac86d3f722b08a22dd945faac4e","abstract_canon_sha256":"bbaa93164002d5cdedad9e959db3b655e41e30d29f4c542f6d6e7234bd67a2f9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:45:12.582300Z","signature_b64":"9/Vt+N4O52zmfUPOfW6FX4GtZsc8G/OWT0/oRIfOn3pRKYd7VIQGJtNcaQGI8p/mgEUXEabebcDdQ/4bU1l2Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"57b716f75053ad7382786e5166e3254be04f9fbec2c34e070e38bc385b960c13","last_reissued_at":"2026-07-05T09:45:12.581719Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:45:12.581719Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Lost and Found: Overcoming Detector Failures in Online Multi-Object Tracking","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Lorenzo Vaquero, Manuel Mucientes, Victor M. Brea, Xavier Alameda-Pineda, Yihong Xu","submitted_at":"2024-07-14T10:45:12Z","abstract_excerpt":"Multi-object tracking (MOT) endeavors to precisely estimate the positions and identities of multiple objects over time. The prevailing approach, tracking-by-detection (TbD), first detects objects and then links detections, resulting in a simple yet effective method. However, contemporary detectors may occasionally miss some objects in certain frames, causing trackers to cease tracking prematurely. To tackle this issue, we propose BUSCA, meaning `to search', a versatile framework compatible with any online TbD system, enhancing its ability to persistently track those objects missed by the detec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.10151","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2407.10151/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2407.10151","created_at":"2026-07-05T09:45:12.581825+00:00"},{"alias_kind":"arxiv_version","alias_value":"2407.10151v2","created_at":"2026-07-05T09:45:12.581825+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.10151","created_at":"2026-07-05T09:45:12.581825+00:00"},{"alias_kind":"pith_short_12","alias_value":"K63RN52QKOWX","created_at":"2026-07-05T09:45:12.581825+00:00"},{"alias_kind":"pith_short_16","alias_value":"K63RN52QKOWXHATY","created_at":"2026-07-05T09:45:12.581825+00:00"},{"alias_kind":"pith_short_8","alias_value":"K63RN52Q","created_at":"2026-07-05T09:45:12.581825+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.01257","citing_title":"CAMELTrack: Context-Aware Multi-cue ExpLoitation for Online Multi-Object Tracking","ref_index":58,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/K63RN52QKOWXHATYNZIWNYZFJP","json":"https://pith.science/pith/K63RN52QKOWXHATYNZIWNYZFJP.json","graph_json":"https://pith.science/api/pith-number/K63RN52QKOWXHATYNZIWNYZFJP/graph.json","events_json":"https://pith.science/api/pith-number/K63RN52QKOWXHATYNZIWNYZFJP/events.json","paper":"https://pith.science/paper/K63RN52Q"},"agent_actions":{"view_html":"https://pith.science/pith/K63RN52QKOWXHATYNZIWNYZFJP","download_json":"https://pith.science/pith/K63RN52QKOWXHATYNZIWNYZFJP.json","view_paper":"https://pith.science/paper/K63RN52Q","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2407.10151&json=true","fetch_graph":"https://pith.science/api/pith-number/K63RN52QKOWXHATYNZIWNYZFJP/graph.json","fetch_events":"https://pith.science/api/pith-number/K63RN52QKOWXHATYNZIWNYZFJP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/K63RN52QKOWXHATYNZIWNYZFJP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/K63RN52QKOWXHATYNZIWNYZFJP/action/storage_attestation","attest_author":"https://pith.science/pith/K63RN52QKOWXHATYNZIWNYZFJP/action/author_attestation","sign_citation":"https://pith.science/pith/K63RN52QKOWXHATYNZIWNYZFJP/action/citation_signature","submit_replication":"https://pith.science/pith/K63RN52QKOWXHATYNZIWNYZFJP/action/replication_record"}},"created_at":"2026-07-05T09:45:12.581825+00:00","updated_at":"2026-07-05T09:45:12.581825+00:00"}