{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:7P5U5Y5YXRRLJXB4GW4NSERMF2","short_pith_number":"pith:7P5U5Y5Y","schema_version":"1.0","canonical_sha256":"fbfb4ee3b8bc62b4dc3c35b8d9122c2ead56bba91a65b3b838f07f0166ffb7b7","source":{"kind":"arxiv","id":"2203.01885","version":3},"attestation_state":"computed","paper":{"title":"TCTrack: Temporal Contexts for Aerial Tracking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Changhong Fu, Liang Pan, Shiwei Zhang, Ziang Cao, Ziwei Liu, Ziyuan Huang","submitted_at":"2022-03-03T18:04:20Z","abstract_excerpt":"Temporal contexts among consecutive frames are far from being fully utilized in existing visual trackers. In this work, we present TCTrack, a comprehensive framework to fully exploit temporal contexts for aerial tracking. The temporal contexts are incorporated at \\textbf{two levels}: the extraction of \\textbf{features} and the refinement of \\textbf{similarity maps}. Specifically, for feature extraction, an online temporally adaptive convolution is proposed to enhance the spatial features using temporal information, which is achieved by dynamically calibrating the convolution weights according "},"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":"2203.01885","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-03T18:04:20Z","cross_cats_sorted":[],"title_canon_sha256":"a04588ca693834cf6b12f1eee2f8fa8836ab11d6533768eeaac080ec0d8359d3","abstract_canon_sha256":"8d62785bc2c97fa500cd621fd2788d8850df7e6f82b47e19758506bb4b0938fd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:09:02.352888Z","signature_b64":"kwjnXv3icy5/JXHrXel9rMMaZXYtPrVVLR4009xmzalRv2LMDIBPTYYI4oYijlM5koX9LcuuhgyUGfx0uEUODw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fbfb4ee3b8bc62b4dc3c35b8d9122c2ead56bba91a65b3b838f07f0166ffb7b7","last_reissued_at":"2026-07-05T04:09:02.352440Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:09:02.352440Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"TCTrack: Temporal Contexts for Aerial Tracking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Changhong Fu, Liang Pan, Shiwei Zhang, Ziang Cao, Ziwei Liu, Ziyuan Huang","submitted_at":"2022-03-03T18:04:20Z","abstract_excerpt":"Temporal contexts among consecutive frames are far from being fully utilized in existing visual trackers. In this work, we present TCTrack, a comprehensive framework to fully exploit temporal contexts for aerial tracking. The temporal contexts are incorporated at \\textbf{two levels}: the extraction of \\textbf{features} and the refinement of \\textbf{similarity maps}. Specifically, for feature extraction, an online temporally adaptive convolution is proposed to enhance the spatial features using temporal information, which is achieved by dynamically calibrating the convolution weights according "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.01885","kind":"arxiv","version":3},"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/2203.01885/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":"2203.01885","created_at":"2026-07-05T04:09:02.352498+00:00"},{"alias_kind":"arxiv_version","alias_value":"2203.01885v3","created_at":"2026-07-05T04:09:02.352498+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.01885","created_at":"2026-07-05T04:09:02.352498+00:00"},{"alias_kind":"pith_short_12","alias_value":"7P5U5Y5YXRRL","created_at":"2026-07-05T04:09:02.352498+00:00"},{"alias_kind":"pith_short_16","alias_value":"7P5U5Y5YXRRLJXB4","created_at":"2026-07-05T04:09:02.352498+00:00"},{"alias_kind":"pith_short_8","alias_value":"7P5U5Y5Y","created_at":"2026-07-05T04:09:02.352498+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7P5U5Y5YXRRLJXB4GW4NSERMF2","json":"https://pith.science/pith/7P5U5Y5YXRRLJXB4GW4NSERMF2.json","graph_json":"https://pith.science/api/pith-number/7P5U5Y5YXRRLJXB4GW4NSERMF2/graph.json","events_json":"https://pith.science/api/pith-number/7P5U5Y5YXRRLJXB4GW4NSERMF2/events.json","paper":"https://pith.science/paper/7P5U5Y5Y"},"agent_actions":{"view_html":"https://pith.science/pith/7P5U5Y5YXRRLJXB4GW4NSERMF2","download_json":"https://pith.science/pith/7P5U5Y5YXRRLJXB4GW4NSERMF2.json","view_paper":"https://pith.science/paper/7P5U5Y5Y","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2203.01885&json=true","fetch_graph":"https://pith.science/api/pith-number/7P5U5Y5YXRRLJXB4GW4NSERMF2/graph.json","fetch_events":"https://pith.science/api/pith-number/7P5U5Y5YXRRLJXB4GW4NSERMF2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7P5U5Y5YXRRLJXB4GW4NSERMF2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7P5U5Y5YXRRLJXB4GW4NSERMF2/action/storage_attestation","attest_author":"https://pith.science/pith/7P5U5Y5YXRRLJXB4GW4NSERMF2/action/author_attestation","sign_citation":"https://pith.science/pith/7P5U5Y5YXRRLJXB4GW4NSERMF2/action/citation_signature","submit_replication":"https://pith.science/pith/7P5U5Y5YXRRLJXB4GW4NSERMF2/action/replication_record"}},"created_at":"2026-07-05T04:09:02.352498+00:00","updated_at":"2026-07-05T04:09:02.352498+00:00"}