{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GTILWKE5XQ5A46BRG5XEEIFIMC","short_pith_number":"pith:GTILWKE5","canonical_record":{"source":{"id":"2401.10643","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-01-19T11:45:10Z","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"title_canon_sha256":"7365e995d826777d6df7bd0d7e0343be97f587af1ef0a587a6a782bef7be7492","abstract_canon_sha256":"0ad5f35be24d7655675284db9846285669c3dce05f9319a3cb2f3ecc4ae863b9"},"schema_version":"1.0"},"canonical_sha256":"34d0bb289dbc3a0e7831376e4220a8609ce77a4b90f7ece7d82fb87cf392bb0c","source":{"kind":"arxiv","id":"2401.10643","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.10643","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"arxiv_version","alias_value":"2401.10643v1","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.10643","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"pith_short_12","alias_value":"GTILWKE5XQ5A","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"pith_short_16","alias_value":"GTILWKE5XQ5A46BR","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"pith_short_8","alias_value":"GTILWKE5","created_at":"2026-07-05T07:35:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GTILWKE5XQ5A46BRG5XEEIFIMC","target":"record","payload":{"canonical_record":{"source":{"id":"2401.10643","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-01-19T11:45:10Z","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"title_canon_sha256":"7365e995d826777d6df7bd0d7e0343be97f587af1ef0a587a6a782bef7be7492","abstract_canon_sha256":"0ad5f35be24d7655675284db9846285669c3dce05f9319a3cb2f3ecc4ae863b9"},"schema_version":"1.0"},"canonical_sha256":"34d0bb289dbc3a0e7831376e4220a8609ce77a4b90f7ece7d82fb87cf392bb0c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:35:29.523121Z","signature_b64":"zRyTDlZyph3TyqJ6qdSqvVRiNGLVlftoarixm8qwdlygjSSXkyf0/b9GwEJ29B/rH427IWuCM/b2t1N3MpL0Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"34d0bb289dbc3a0e7831376e4220a8609ce77a4b90f7ece7d82fb87cf392bb0c","last_reissued_at":"2026-07-05T07:35:29.522729Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:35:29.522729Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.10643","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":"2026-07-05T07:35:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O1Jzc5EiTyPsJS8j/rC9yd2/65nFDaN48T1QTbQ6nEQSu14JuU/yxByyHKrp/ArvazK2/GHTIqm0Xx6LbGFkBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T19:17:59.220198Z"},"content_sha256":"b1e6ad885475062c4336e653c27bfe9d60ff5c8542e7d912d5acd2b112d2ca06","schema_version":"1.0","event_id":"sha256:b1e6ad885475062c4336e653c27bfe9d60ff5c8542e7d912d5acd2b112d2ca06"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GTILWKE5XQ5A46BRG5XEEIFIMC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Comprehensive Survey on Deep-Learning-based Vehicle Re-Identification: Models, Data Sets and Challenges","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","eess.IV"],"primary_cat":"cs.CV","authors_text":"Ali Amiri, Ali Seydi Keceli, Aydin Kaya","submitted_at":"2024-01-19T11:45:10Z","abstract_excerpt":"Vehicle re-identification (ReID) endeavors to associate vehicle images collected from a distributed network of cameras spanning diverse traffic environments. This task assumes paramount importance within the spectrum of vehicle-centric technologies, playing a pivotal role in deploying Intelligent Transportation Systems (ITS) and advancing smart city initiatives. Rapid advancements in deep learning have significantly propelled the evolution of vehicle ReID technologies in recent years. Consequently, undertaking a comprehensive survey of methodologies centered on deep learning for vehicle re-ide"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.10643","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/2401.10643/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":"2026-07-05T07:35:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"otGSeG0AMNa0IvcIcLzMo7xQGZd2oWT34ei9XUtrfMgwO+wdt3W+voEct7iqC+pKmbRmVnZZLXhWN5jZUhEtBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T19:17:59.223245Z"},"content_sha256":"20205b75c5202c5e0a1cc3f8457a8556ef2be7b628cc3434ce51b5ec3a6eaecc","schema_version":"1.0","event_id":"sha256:20205b75c5202c5e0a1cc3f8457a8556ef2be7b628cc3434ce51b5ec3a6eaecc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GTILWKE5XQ5A46BRG5XEEIFIMC/bundle.json","state_url":"https://pith.science/pith/GTILWKE5XQ5A46BRG5XEEIFIMC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GTILWKE5XQ5A46BRG5XEEIFIMC/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":"2026-08-17T19:17:59Z","links":{"resolver":"https://pith.science/pith/GTILWKE5XQ5A46BRG5XEEIFIMC","bundle":"https://pith.science/pith/GTILWKE5XQ5A46BRG5XEEIFIMC/bundle.json","state":"https://pith.science/pith/GTILWKE5XQ5A46BRG5XEEIFIMC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GTILWKE5XQ5A46BRG5XEEIFIMC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GTILWKE5XQ5A46BRG5XEEIFIMC","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":"0ad5f35be24d7655675284db9846285669c3dce05f9319a3cb2f3ecc4ae863b9","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-01-19T11:45:10Z","title_canon_sha256":"7365e995d826777d6df7bd0d7e0343be97f587af1ef0a587a6a782bef7be7492"},"schema_version":"1.0","source":{"id":"2401.10643","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.10643","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"arxiv_version","alias_value":"2401.10643v1","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.10643","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"pith_short_12","alias_value":"GTILWKE5XQ5A","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"pith_short_16","alias_value":"GTILWKE5XQ5A46BR","created_at":"2026-07-05T07:35:29Z"},{"alias_kind":"pith_short_8","alias_value":"GTILWKE5","created_at":"2026-07-05T07:35:29Z"}],"graph_snapshots":[{"event_id":"sha256:20205b75c5202c5e0a1cc3f8457a8556ef2be7b628cc3434ce51b5ec3a6eaecc","target":"graph","created_at":"2026-07-05T07:35:29Z","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/2401.10643/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vehicle re-identification (ReID) endeavors to associate vehicle images collected from a distributed network of cameras spanning diverse traffic environments. This task assumes paramount importance within the spectrum of vehicle-centric technologies, playing a pivotal role in deploying Intelligent Transportation Systems (ITS) and advancing smart city initiatives. Rapid advancements in deep learning have significantly propelled the evolution of vehicle ReID technologies in recent years. Consequently, undertaking a comprehensive survey of methodologies centered on deep learning for vehicle re-ide","authors_text":"Ali Amiri, Ali Seydi Keceli, Aydin Kaya","cross_cats":["cs.AI","cs.LG","eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-01-19T11:45:10Z","title":"A Comprehensive Survey on Deep-Learning-based Vehicle Re-Identification: Models, Data Sets and Challenges"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.10643","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:b1e6ad885475062c4336e653c27bfe9d60ff5c8542e7d912d5acd2b112d2ca06","target":"record","created_at":"2026-07-05T07:35:29Z","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":"0ad5f35be24d7655675284db9846285669c3dce05f9319a3cb2f3ecc4ae863b9","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-01-19T11:45:10Z","title_canon_sha256":"7365e995d826777d6df7bd0d7e0343be97f587af1ef0a587a6a782bef7be7492"},"schema_version":"1.0","source":{"id":"2401.10643","kind":"arxiv","version":1}},"canonical_sha256":"34d0bb289dbc3a0e7831376e4220a8609ce77a4b90f7ece7d82fb87cf392bb0c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"34d0bb289dbc3a0e7831376e4220a8609ce77a4b90f7ece7d82fb87cf392bb0c","first_computed_at":"2026-07-05T07:35:29.522729Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:35:29.522729Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zRyTDlZyph3TyqJ6qdSqvVRiNGLVlftoarixm8qwdlygjSSXkyf0/b9GwEJ29B/rH427IWuCM/b2t1N3MpL0Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T07:35:29.523121Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.10643","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b1e6ad885475062c4336e653c27bfe9d60ff5c8542e7d912d5acd2b112d2ca06","sha256:20205b75c5202c5e0a1cc3f8457a8556ef2be7b628cc3434ce51b5ec3a6eaecc"],"state_sha256":"64a52821cc6ebbd30bc59ec4638f3c4b39e5d3b5c102c300456d327089fd6873"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lE72KFpfsBccRCp58CIbogkIUOQuKbMFcezuJGe7I1+Y7UxNViAhmVcrth0dLeplbgaEVHw4YS+U7DvfcFbiBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T19:17:59.238891Z","bundle_sha256":"896462439f80f9dcb8a2fcab8cb60af0ea2a0519eaf6d10620e02270c9aae815"}}