{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:KM26FLREVCKNIE2U7WM3VHOWYE","short_pith_number":"pith:KM26FLRE","canonical_record":{"source":{"id":"2203.16210","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-30T11:20:38Z","cross_cats_sorted":[],"title_canon_sha256":"2bd287765054b173098140f30fd094a65c582ea55c67236f0125b4abd8ae6c1f","abstract_canon_sha256":"56973017651ab66cc878d8cd0b2c381305c211a1746f8f57d78a2f384bbed850"},"schema_version":"1.0"},"canonical_sha256":"5335e2ae24a894d41354fd99ba9dd6c111a2cbf15b624ff8d35b1bf124325143","source":{"kind":"arxiv","id":"2203.16210","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.16210","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"arxiv_version","alias_value":"2203.16210v1","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.16210","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"pith_short_12","alias_value":"KM26FLREVCKN","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"pith_short_16","alias_value":"KM26FLREVCKNIE2U","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"pith_short_8","alias_value":"KM26FLRE","created_at":"2026-07-05T04:10:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:KM26FLREVCKNIE2U7WM3VHOWYE","target":"record","payload":{"canonical_record":{"source":{"id":"2203.16210","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-30T11:20:38Z","cross_cats_sorted":[],"title_canon_sha256":"2bd287765054b173098140f30fd094a65c582ea55c67236f0125b4abd8ae6c1f","abstract_canon_sha256":"56973017651ab66cc878d8cd0b2c381305c211a1746f8f57d78a2f384bbed850"},"schema_version":"1.0"},"canonical_sha256":"5335e2ae24a894d41354fd99ba9dd6c111a2cbf15b624ff8d35b1bf124325143","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:10:08.634633Z","signature_b64":"pH9h1iHwJBnmrgbZX9sEpcwOVLEwL5sUuOEiDQvhzUinVqwbzwwKcboOKBAbXE5WR6gnBUo+oNxPFNKKUdQbDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5335e2ae24a894d41354fd99ba9dd6c111a2cbf15b624ff8d35b1bf124325143","last_reissued_at":"2026-07-05T04:10:08.634170Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:10:08.634170Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.16210","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:10:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/xtHIj6u3WduLY7DCzpeOiZs3AWSVB8e5dG8DsS7FX0SHGl9K5sCOQeABMAK+y99+yGsOjR+j46zQr37kWHnAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:48:38.580787Z"},"content_sha256":"26ba2f32c26781f1c5b4d19ca8e135b676612122bf58fbb447e1d07db6d2c0ff","schema_version":"1.0","event_id":"sha256:26ba2f32c26781f1c5b4d19ca8e135b676612122bf58fbb447e1d07db6d2c0ff"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:KM26FLREVCKNIE2U7WM3VHOWYE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning of Global Objective for Network Flow in Multi-Object Tracking","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hamid Rezatofighi, Shuai Li, Yu Kong","submitted_at":"2022-03-30T11:20:38Z","abstract_excerpt":"This paper concerns the problem of multi-object tracking based on the min-cost flow (MCF) formulation, which is conventionally studied as an instance of linear program. Given its computationally tractable inference, the success of MCF tracking largely relies on the learned cost function of underlying linear program. Most previous studies focus on learning the cost function by only taking into account two frames during training, therefore the learned cost function is sub-optimal for MCF where a multi-frame data association must be considered during inference. In order to address this problem, i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.16210","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/2203.16210/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":"2026-07-05T04:10:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qjHA3CzHnbUyT9C2NUre0kwgyzAy10zcAeVif2lATo3H9sxS1SZ2fAvTYbkIdjpdGqQNCSrhBoC4EibqNgE6Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:48:38.581510Z"},"content_sha256":"ed8c3633ce937e3ce5c6baa47c8f123ea4a29b44d5d73208bc58260f1b0105ab","schema_version":"1.0","event_id":"sha256:ed8c3633ce937e3ce5c6baa47c8f123ea4a29b44d5d73208bc58260f1b0105ab"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KM26FLREVCKNIE2U7WM3VHOWYE/bundle.json","state_url":"https://pith.science/pith/KM26FLREVCKNIE2U7WM3VHOWYE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KM26FLREVCKNIE2U7WM3VHOWYE/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":"2026-07-07T06:48:38Z","links":{"resolver":"https://pith.science/pith/KM26FLREVCKNIE2U7WM3VHOWYE","bundle":"https://pith.science/pith/KM26FLREVCKNIE2U7WM3VHOWYE/bundle.json","state":"https://pith.science/pith/KM26FLREVCKNIE2U7WM3VHOWYE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KM26FLREVCKNIE2U7WM3VHOWYE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:KM26FLREVCKNIE2U7WM3VHOWYE","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":"56973017651ab66cc878d8cd0b2c381305c211a1746f8f57d78a2f384bbed850","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-30T11:20:38Z","title_canon_sha256":"2bd287765054b173098140f30fd094a65c582ea55c67236f0125b4abd8ae6c1f"},"schema_version":"1.0","source":{"id":"2203.16210","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.16210","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"arxiv_version","alias_value":"2203.16210v1","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.16210","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"pith_short_12","alias_value":"KM26FLREVCKN","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"pith_short_16","alias_value":"KM26FLREVCKNIE2U","created_at":"2026-07-05T04:10:08Z"},{"alias_kind":"pith_short_8","alias_value":"KM26FLRE","created_at":"2026-07-05T04:10:08Z"}],"graph_snapshots":[{"event_id":"sha256:ed8c3633ce937e3ce5c6baa47c8f123ea4a29b44d5d73208bc58260f1b0105ab","target":"graph","created_at":"2026-07-05T04:10:08Z","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/2203.16210/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper concerns the problem of multi-object tracking based on the min-cost flow (MCF) formulation, which is conventionally studied as an instance of linear program. Given its computationally tractable inference, the success of MCF tracking largely relies on the learned cost function of underlying linear program. Most previous studies focus on learning the cost function by only taking into account two frames during training, therefore the learned cost function is sub-optimal for MCF where a multi-frame data association must be considered during inference. In order to address this problem, i","authors_text":"Hamid Rezatofighi, Shuai Li, Yu Kong","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-30T11:20:38Z","title":"Learning of Global Objective for Network Flow in Multi-Object Tracking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.16210","kind":"arxiv","version":1},"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":"sha256:26ba2f32c26781f1c5b4d19ca8e135b676612122bf58fbb447e1d07db6d2c0ff","target":"record","created_at":"2026-07-05T04:10:08Z","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":"56973017651ab66cc878d8cd0b2c381305c211a1746f8f57d78a2f384bbed850","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-30T11:20:38Z","title_canon_sha256":"2bd287765054b173098140f30fd094a65c582ea55c67236f0125b4abd8ae6c1f"},"schema_version":"1.0","source":{"id":"2203.16210","kind":"arxiv","version":1}},"canonical_sha256":"5335e2ae24a894d41354fd99ba9dd6c111a2cbf15b624ff8d35b1bf124325143","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5335e2ae24a894d41354fd99ba9dd6c111a2cbf15b624ff8d35b1bf124325143","first_computed_at":"2026-07-05T04:10:08.634170Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:10:08.634170Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pH9h1iHwJBnmrgbZX9sEpcwOVLEwL5sUuOEiDQvhzUinVqwbzwwKcboOKBAbXE5WR6gnBUo+oNxPFNKKUdQbDg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:10:08.634633Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.16210","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:26ba2f32c26781f1c5b4d19ca8e135b676612122bf58fbb447e1d07db6d2c0ff","sha256:ed8c3633ce937e3ce5c6baa47c8f123ea4a29b44d5d73208bc58260f1b0105ab"],"state_sha256":"a600277b0fb79556e005ebd790a170a113a9c1fed77fa4797f4338297723e975"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zekOHbOwjPm0dD5M/VfXX4XcAUC1OHfUUfngFL4w0772nkBkNr203Xcr+yG0plgk+NyIFHmN1lSbY8/udSOpCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T06:48:38.585446Z","bundle_sha256":"e8e17c155f45097fca7e4347c17a398bee74dae29d5982b6f9baff166ce3f3eb"}}