{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:WCM7KC3YIOBSFJDONLOUZ3MKHH","short_pith_number":"pith:WCM7KC3Y","canonical_record":{"source":{"id":"1905.12409","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-29T13:16:12Z","cross_cats_sorted":[],"title_canon_sha256":"3f6d7bb1521dda9d115d19b35f0b0fc73b444a3d77c561d6821c45cfefcf4ab2","abstract_canon_sha256":"d50e9732cd2b717f7407d3867ad269cbda0de60f9ba4829bf6faf43e0e18f192"},"schema_version":"1.0"},"canonical_sha256":"b099f50b78438322a46e6add4ced8a39ef64070242c839b49a4a2139f886d067","source":{"kind":"arxiv","id":"1905.12409","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.12409","created_at":"2026-05-17T23:44:44Z"},{"alias_kind":"arxiv_version","alias_value":"1905.12409v1","created_at":"2026-05-17T23:44:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.12409","created_at":"2026-05-17T23:44:44Z"},{"alias_kind":"pith_short_12","alias_value":"WCM7KC3YIOBS","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"WCM7KC3YIOBSFJDO","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"WCM7KC3Y","created_at":"2026-05-18T12:33:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:WCM7KC3YIOBSFJDONLOUZ3MKHH","target":"record","payload":{"canonical_record":{"source":{"id":"1905.12409","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-29T13:16:12Z","cross_cats_sorted":[],"title_canon_sha256":"3f6d7bb1521dda9d115d19b35f0b0fc73b444a3d77c561d6821c45cfefcf4ab2","abstract_canon_sha256":"d50e9732cd2b717f7407d3867ad269cbda0de60f9ba4829bf6faf43e0e18f192"},"schema_version":"1.0"},"canonical_sha256":"b099f50b78438322a46e6add4ced8a39ef64070242c839b49a4a2139f886d067","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:44.423302Z","signature_b64":"ZzT7XZTigA/cVhRrtn2PnfVIByz2f7XMv4E9yzfNHK1MBRFQdxXVfVd8UCnALmYe0klUx8C7pdL6eoB7n1Z3DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b099f50b78438322a46e6add4ced8a39ef64070242c839b49a4a2139f886d067","last_reissued_at":"2026-05-17T23:44:44.422828Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:44.422828Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.12409","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":"2026-05-17T23:44:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XdUjXC5vBvRVwIqT34pOrMGxBfDAig9xVttjKeQvOlf0R5K0zcSY0Ep56MCEnPayryfWNZ12gWEEDCcyi3ibBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T23:26:39.571705Z"},"content_sha256":"927fed967ff6c39d1a1f76e35445680c6e2d7c5da87125ae6bae594851177656","schema_version":"1.0","event_id":"sha256:927fed967ff6c39d1a1f76e35445680c6e2d7c5da87125ae6bae594851177656"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:WCM7KC3YIOBSFJDONLOUZ3MKHH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Instance-Aware Representation Learning and Association for Online Multi-Person Tracking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hanhui Li, Hefeng Wu, Hui Cheng, Keze Wang, Lin Nie, Yafei Hu","submitted_at":"2019-05-29T13:16:12Z","abstract_excerpt":"Multi-Person Tracking (MPT) is often addressed within the detection-to-association paradigm. In such approaches, human detections are first extracted in every frame and person trajectories are then recovered by a procedure of data association (usually offline). However, their performances usually degenerate in presence of detection errors, mutual interactions and occlusions. In this paper, we present a deep learning based MPT approach that learns instance-aware representations of tracked persons and robustly online infers states of the tracked persons. Specifically, we design a multi-branch ne"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.12409","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":""},"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":"2026-05-17T23:44:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1NP1U8SPF3F6CaEuV2RKbAZZjcYv7o4Lh36pXjjgdkA9OUPEdTSnqO67twYO/rKa9sP08Hod4A2+IS9CtcxMAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T23:26:39.572477Z"},"content_sha256":"20a4ed4a56f2bdb6a23a8c29fa05bd5ee2c31608d5497a6a67c75c686cc81847","schema_version":"1.0","event_id":"sha256:20a4ed4a56f2bdb6a23a8c29fa05bd5ee2c31608d5497a6a67c75c686cc81847"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WCM7KC3YIOBSFJDONLOUZ3MKHH/bundle.json","state_url":"https://pith.science/pith/WCM7KC3YIOBSFJDONLOUZ3MKHH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WCM7KC3YIOBSFJDONLOUZ3MKHH/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":"2026-05-31T23:26:39Z","links":{"resolver":"https://pith.science/pith/WCM7KC3YIOBSFJDONLOUZ3MKHH","bundle":"https://pith.science/pith/WCM7KC3YIOBSFJDONLOUZ3MKHH/bundle.json","state":"https://pith.science/pith/WCM7KC3YIOBSFJDONLOUZ3MKHH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WCM7KC3YIOBSFJDONLOUZ3MKHH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:WCM7KC3YIOBSFJDONLOUZ3MKHH","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":"d50e9732cd2b717f7407d3867ad269cbda0de60f9ba4829bf6faf43e0e18f192","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-29T13:16:12Z","title_canon_sha256":"3f6d7bb1521dda9d115d19b35f0b0fc73b444a3d77c561d6821c45cfefcf4ab2"},"schema_version":"1.0","source":{"id":"1905.12409","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.12409","created_at":"2026-05-17T23:44:44Z"},{"alias_kind":"arxiv_version","alias_value":"1905.12409v1","created_at":"2026-05-17T23:44:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.12409","created_at":"2026-05-17T23:44:44Z"},{"alias_kind":"pith_short_12","alias_value":"WCM7KC3YIOBS","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"WCM7KC3YIOBSFJDO","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"WCM7KC3Y","created_at":"2026-05-18T12:33:30Z"}],"graph_snapshots":[{"event_id":"sha256:20a4ed4a56f2bdb6a23a8c29fa05bd5ee2c31608d5497a6a67c75c686cc81847","target":"graph","created_at":"2026-05-17T23:44:44Z","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"},"paper":{"abstract_excerpt":"Multi-Person Tracking (MPT) is often addressed within the detection-to-association paradigm. In such approaches, human detections are first extracted in every frame and person trajectories are then recovered by a procedure of data association (usually offline). However, their performances usually degenerate in presence of detection errors, mutual interactions and occlusions. In this paper, we present a deep learning based MPT approach that learns instance-aware representations of tracked persons and robustly online infers states of the tracked persons. Specifically, we design a multi-branch ne","authors_text":"Hanhui Li, Hefeng Wu, Hui Cheng, Keze Wang, Lin Nie, Yafei Hu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-29T13:16:12Z","title":"Instance-Aware Representation Learning and Association for Online Multi-Person Tracking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.12409","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":"sha256:927fed967ff6c39d1a1f76e35445680c6e2d7c5da87125ae6bae594851177656","target":"record","created_at":"2026-05-17T23:44:44Z","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":"d50e9732cd2b717f7407d3867ad269cbda0de60f9ba4829bf6faf43e0e18f192","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-29T13:16:12Z","title_canon_sha256":"3f6d7bb1521dda9d115d19b35f0b0fc73b444a3d77c561d6821c45cfefcf4ab2"},"schema_version":"1.0","source":{"id":"1905.12409","kind":"arxiv","version":1}},"canonical_sha256":"b099f50b78438322a46e6add4ced8a39ef64070242c839b49a4a2139f886d067","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b099f50b78438322a46e6add4ced8a39ef64070242c839b49a4a2139f886d067","first_computed_at":"2026-05-17T23:44:44.422828Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:44.422828Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZzT7XZTigA/cVhRrtn2PnfVIByz2f7XMv4E9yzfNHK1MBRFQdxXVfVd8UCnALmYe0klUx8C7pdL6eoB7n1Z3DA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:44.423302Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.12409","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:927fed967ff6c39d1a1f76e35445680c6e2d7c5da87125ae6bae594851177656","sha256:20a4ed4a56f2bdb6a23a8c29fa05bd5ee2c31608d5497a6a67c75c686cc81847"],"state_sha256":"c6392d9e95b141c59158c66bf25c97f41e7429ac53ecefed1f44ffdbae51e9ab"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ah+qst7I9FwcXJEzUTXDv1bWoOivw1LE627PmeMJwoURHk+P2HE/lguz/5ESRQN09etGy9DDFCXA/zg+P7JSCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T23:26:39.578980Z","bundle_sha256":"33f182aa9840dbd024ae9249a979c25845665cb21e7abb42562025a0169e3d1a"}}