{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:EWNOIZ5RJPPUSYG3FGD5G4YRYO","short_pith_number":"pith:EWNOIZ5R","canonical_record":{"source":{"id":"2410.24211","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T17:59:01Z","cross_cats_sorted":[],"title_canon_sha256":"38e37d252c873ffdcaf2f512bb4c1eb1d07a0c82dd3c8c3ec54f9a601456f82d","abstract_canon_sha256":"1b215a896318690ac06481a9617e0fb229bc923b50f8283d7f8699f6f2ba8417"},"schema_version":"1.0"},"canonical_sha256":"259ae467b14bdf4960db2987d37311c3846bbf8aa532fa4e5fe82c5a4ab55b67","source":{"kind":"arxiv","id":"2410.24211","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.24211","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"arxiv_version","alias_value":"2410.24211v3","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.24211","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"pith_short_12","alias_value":"EWNOIZ5RJPPU","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"pith_short_16","alias_value":"EWNOIZ5RJPPUSYG3","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"pith_short_8","alias_value":"EWNOIZ5R","created_at":"2026-07-05T10:21:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:EWNOIZ5RJPPUSYG3FGD5G4YRYO","target":"record","payload":{"canonical_record":{"source":{"id":"2410.24211","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T17:59:01Z","cross_cats_sorted":[],"title_canon_sha256":"38e37d252c873ffdcaf2f512bb4c1eb1d07a0c82dd3c8c3ec54f9a601456f82d","abstract_canon_sha256":"1b215a896318690ac06481a9617e0fb229bc923b50f8283d7f8699f6f2ba8417"},"schema_version":"1.0"},"canonical_sha256":"259ae467b14bdf4960db2987d37311c3846bbf8aa532fa4e5fe82c5a4ab55b67","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:21:52.159359Z","signature_b64":"js4oGKqMmHAlbHGY3KU3A/CHMyvDs/SNdZEKRMdhrRFNAC7TR11CUS65xx9f/Imtz1Vba5zOLxp6QCt4D16FBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"259ae467b14bdf4960db2987d37311c3846bbf8aa532fa4e5fe82c5a4ab55b67","last_reissued_at":"2026-07-05T10:21:52.158854Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:21:52.158854Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.24211","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:21:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0jYKLudTtUPd8gw0HF2DsX8gU0IsputFDN2DUEHkPVpJ6ZTPh3dOCZGtbLPa0QEA+6I+gWLf10F8ephnw+JcBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:46:46.898362Z"},"content_sha256":"adb813b95e97c80b0d3fbde1a55e15b6e59fb4f74134f52e83fd59e9e500b8ce","schema_version":"1.0","event_id":"sha256:adb813b95e97c80b0d3fbde1a55e15b6e59fb4f74134f52e83fd59e9e500b8ce"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:EWNOIZ5RJPPUSYG3FGD5G4YRYO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DELTA: Dense Efficient Long-range 3D Tracking for any video","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chaoyang Wang, Chuang Gan, Evangelos Kalogerakis, Hsin-Ying Lee, Peiye Zhuang, Sergey Tulyakov, Tuan Duc Ngo","submitted_at":"2024-10-31T17:59:01Z","abstract_excerpt":"Tracking dense 3D motion from monocular videos remains challenging, particularly when aiming for pixel-level precision over long sequences. We introduce DELTA, a novel method that efficiently tracks every pixel in 3D space, enabling accurate motion estimation across entire videos. Our approach leverages a joint global-local attention mechanism for reduced-resolution tracking, followed by a transformer-based upsampler to achieve high-resolution predictions. Unlike existing methods, which are limited by computational inefficiency or sparse tracking, DELTA delivers dense 3D tracking at scale, run"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.24211","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/2410.24211/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:21:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zUzpZveRoiyQRmYZxv0TAJaYd/nWUQYKVDiQhrbVEhNTnMhm7LAMFuRoMoySW4yB4bTBLyYk7Z0v1Ka9eoIeAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:46:46.898877Z"},"content_sha256":"c8163d6b6b9cce30cd1ee27349bc3944b1f84dcdbbb12eff127037bc0ea40456","schema_version":"1.0","event_id":"sha256:c8163d6b6b9cce30cd1ee27349bc3944b1f84dcdbbb12eff127037bc0ea40456"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EWNOIZ5RJPPUSYG3FGD5G4YRYO/bundle.json","state_url":"https://pith.science/pith/EWNOIZ5RJPPUSYG3FGD5G4YRYO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EWNOIZ5RJPPUSYG3FGD5G4YRYO/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T15:46:46Z","links":{"resolver":"https://pith.science/pith/EWNOIZ5RJPPUSYG3FGD5G4YRYO","bundle":"https://pith.science/pith/EWNOIZ5RJPPUSYG3FGD5G4YRYO/bundle.json","state":"https://pith.science/pith/EWNOIZ5RJPPUSYG3FGD5G4YRYO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EWNOIZ5RJPPUSYG3FGD5G4YRYO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:EWNOIZ5RJPPUSYG3FGD5G4YRYO","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"1b215a896318690ac06481a9617e0fb229bc923b50f8283d7f8699f6f2ba8417","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T17:59:01Z","title_canon_sha256":"38e37d252c873ffdcaf2f512bb4c1eb1d07a0c82dd3c8c3ec54f9a601456f82d"},"schema_version":"1.0","source":{"id":"2410.24211","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.24211","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"arxiv_version","alias_value":"2410.24211v3","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.24211","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"pith_short_12","alias_value":"EWNOIZ5RJPPU","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"pith_short_16","alias_value":"EWNOIZ5RJPPUSYG3","created_at":"2026-07-05T10:21:52Z"},{"alias_kind":"pith_short_8","alias_value":"EWNOIZ5R","created_at":"2026-07-05T10:21:52Z"}],"graph_snapshots":[{"event_id":"sha256:c8163d6b6b9cce30cd1ee27349bc3944b1f84dcdbbb12eff127037bc0ea40456","target":"graph","created_at":"2026-07-05T10:21:52Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2410.24211/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Tracking dense 3D motion from monocular videos remains challenging, particularly when aiming for pixel-level precision over long sequences. We introduce DELTA, a novel method that efficiently tracks every pixel in 3D space, enabling accurate motion estimation across entire videos. Our approach leverages a joint global-local attention mechanism for reduced-resolution tracking, followed by a transformer-based upsampler to achieve high-resolution predictions. Unlike existing methods, which are limited by computational inefficiency or sparse tracking, DELTA delivers dense 3D tracking at scale, run","authors_text":"Chaoyang Wang, Chuang Gan, Evangelos Kalogerakis, Hsin-Ying Lee, Peiye Zhuang, Sergey Tulyakov, Tuan Duc Ngo","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T17:59:01Z","title":"DELTA: Dense Efficient Long-range 3D Tracking for any video"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.24211","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:adb813b95e97c80b0d3fbde1a55e15b6e59fb4f74134f52e83fd59e9e500b8ce","target":"record","created_at":"2026-07-05T10:21:52Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"1b215a896318690ac06481a9617e0fb229bc923b50f8283d7f8699f6f2ba8417","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T17:59:01Z","title_canon_sha256":"38e37d252c873ffdcaf2f512bb4c1eb1d07a0c82dd3c8c3ec54f9a601456f82d"},"schema_version":"1.0","source":{"id":"2410.24211","kind":"arxiv","version":3}},"canonical_sha256":"259ae467b14bdf4960db2987d37311c3846bbf8aa532fa4e5fe82c5a4ab55b67","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"259ae467b14bdf4960db2987d37311c3846bbf8aa532fa4e5fe82c5a4ab55b67","first_computed_at":"2026-07-05T10:21:52.158854Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:21:52.158854Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"js4oGKqMmHAlbHGY3KU3A/CHMyvDs/SNdZEKRMdhrRFNAC7TR11CUS65xx9f/Imtz1Vba5zOLxp6QCt4D16FBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:21:52.159359Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.24211","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:adb813b95e97c80b0d3fbde1a55e15b6e59fb4f74134f52e83fd59e9e500b8ce","sha256:c8163d6b6b9cce30cd1ee27349bc3944b1f84dcdbbb12eff127037bc0ea40456"],"state_sha256":"097f8e353657ddcb73ca9696e25274b486841772db7878af55e433d3dda27442"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S7rJdwZxCcY1JfU/TRsfgm5K+9BtewwxNoEg5kaZXCu9amD78ZLRpR//QksTigNr6v7UYiMFy+Jy8cCzZEYXDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:46:46.904134Z","bundle_sha256":"0f050c2c43ac67de85e41c7a6718e9f3de83a066c0bca5345135b7a40881f021"}}