{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:VIJ6KZ6YB5YPP4WS7RAFOQNZ6B","short_pith_number":"pith:VIJ6KZ6Y","schema_version":"1.0","canonical_sha256":"aa13e567d80f70f7f2d2fc405741b9f070037c6df5b2e5f09ac9e238646d2c8a","source":{"kind":"arxiv","id":"2607.23669","version":1},"attestation_state":"computed","paper":{"title":"RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Junyue Li, Xuelong Li, Ye Zheng, Yifan Chen, Zhe Sun","submitted_at":"2026-07-26T14:05:46Z","abstract_excerpt":"Robust object 6D pose tracking is critical for robotic systems operating in dynamic and occluded scenes. Per-frame estimators are accurate but computationally expensive, while current trackers struggle with fast motion and complete occlusion due to their reliance on continuous visibility. To address these challenges, we present RRTrack, an efficient, recoverable object 6D pose tracker that enables robust tracking through fast motion and target disappearance--reappearance. RRTrack introduces a 2D--6D closed-loop tracking strategy that integrates memory-based video object segmentation (VOS) with"},"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":"2607.23669","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-26T14:05:46Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"5e038167bfc2577b493178b39725036e7ec8284385bfc1fdf4017eff332ad9e0","abstract_canon_sha256":"3eb88f3c02637551c35256f3cbcbe348a87d049bb646b7164dfd8c241531e307"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-28T01:23:04.560712Z","signature_b64":"qbbzMm/aON/TlAabt5LglTV7qtTeLkyDHvUa63IlBo65NU1oF3cjaMZl8WDHVVSYUhvMAIuzLOKX8u/zAwIrAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa13e567d80f70f7f2d2fc405741b9f070037c6df5b2e5f09ac9e238646d2c8a","last_reissued_at":"2026-07-28T01:23:04.559782Z","signature_status":"signed_v1","first_computed_at":"2026-07-28T01:23:04.559782Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Junyue Li, Xuelong Li, Ye Zheng, Yifan Chen, Zhe Sun","submitted_at":"2026-07-26T14:05:46Z","abstract_excerpt":"Robust object 6D pose tracking is critical for robotic systems operating in dynamic and occluded scenes. Per-frame estimators are accurate but computationally expensive, while current trackers struggle with fast motion and complete occlusion due to their reliance on continuous visibility. To address these challenges, we present RRTrack, an efficient, recoverable object 6D pose tracker that enables robust tracking through fast motion and target disappearance--reappearance. RRTrack introduces a 2D--6D closed-loop tracking strategy that integrates memory-based video object segmentation (VOS) with"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.23669","kind":"arxiv","version":1},"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/2607.23669/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":"2607.23669","created_at":"2026-07-28T01:23:04.560301+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.23669v1","created_at":"2026-07-28T01:23:04.560301+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.23669","created_at":"2026-07-28T01:23:04.560301+00:00"},{"alias_kind":"pith_short_12","alias_value":"VIJ6KZ6YB5YP","created_at":"2026-07-28T01:23:04.560301+00:00"},{"alias_kind":"pith_short_16","alias_value":"VIJ6KZ6YB5YPP4WS","created_at":"2026-07-28T01:23:04.560301+00:00"},{"alias_kind":"pith_short_8","alias_value":"VIJ6KZ6Y","created_at":"2026-07-28T01:23:04.560301+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/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B","json":"https://pith.science/pith/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B.json","graph_json":"https://pith.science/api/pith-number/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B/graph.json","events_json":"https://pith.science/api/pith-number/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B/events.json","paper":"https://pith.science/paper/VIJ6KZ6Y"},"agent_actions":{"view_html":"https://pith.science/pith/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B","download_json":"https://pith.science/pith/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B.json","view_paper":"https://pith.science/paper/VIJ6KZ6Y","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.23669&json=true","fetch_graph":"https://pith.science/api/pith-number/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B/graph.json","fetch_events":"https://pith.science/api/pith-number/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B/action/storage_attestation","attest_author":"https://pith.science/pith/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B/action/author_attestation","sign_citation":"https://pith.science/pith/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B/action/citation_signature","submit_replication":"https://pith.science/pith/VIJ6KZ6YB5YPP4WS7RAFOQNZ6B/action/replication_record"}},"created_at":"2026-07-28T01:23:04.560301+00:00","updated_at":"2026-07-28T01:23:04.560301+00:00"}