{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:GQ332FR665PAYXFOU3HA5ONDUC","short_pith_number":"pith:GQ332FR6","canonical_record":{"source":{"id":"1604.01850","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2016-04-07T02:16:26Z","cross_cats_sorted":[],"title_canon_sha256":"2a6f9c09eaad91e0afcc1e80470ea8f71085f41c6f586960be24d763b07145f1","abstract_canon_sha256":"de2d27ca7542b07fb9cb5d65917d8977bfd769d0d097140aaa4741e250fd514e"},"schema_version":"1.0"},"canonical_sha256":"3437bd163ef75e0c5caea6ce0eb9a3a09d9f8205be1becf2c5e33bbd420fffff","source":{"kind":"arxiv","id":"1604.01850","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.01850","created_at":"2026-05-18T00:46:55Z"},{"alias_kind":"arxiv_version","alias_value":"1604.01850v3","created_at":"2026-05-18T00:46:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.01850","created_at":"2026-05-18T00:46:55Z"},{"alias_kind":"pith_short_12","alias_value":"GQ332FR665PA","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_16","alias_value":"GQ332FR665PAYXFO","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_8","alias_value":"GQ332FR6","created_at":"2026-05-18T12:30:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:GQ332FR665PAYXFOU3HA5ONDUC","target":"record","payload":{"canonical_record":{"source":{"id":"1604.01850","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2016-04-07T02:16:26Z","cross_cats_sorted":[],"title_canon_sha256":"2a6f9c09eaad91e0afcc1e80470ea8f71085f41c6f586960be24d763b07145f1","abstract_canon_sha256":"de2d27ca7542b07fb9cb5d65917d8977bfd769d0d097140aaa4741e250fd514e"},"schema_version":"1.0"},"canonical_sha256":"3437bd163ef75e0c5caea6ce0eb9a3a09d9f8205be1becf2c5e33bbd420fffff","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:46:55.766572Z","signature_b64":"x0lE7lXDzMranfEYrXGXAcl+dN3QWoN6MKmyn2jamYLqEM+fezyPm08TpE0qFokJuut6Y/qL0cqeUI1Co8RCDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3437bd163ef75e0c5caea6ce0eb9a3a09d9f8205be1becf2c5e33bbd420fffff","last_reissued_at":"2026-05-18T00:46:55.766152Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:46:55.766152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1604.01850","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":"2026-05-18T00:46:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+H+zft3t4SClgRQUHWqY3UwJVS+VJcHJr88FIAx77lXtJJ42sZv++XmppFpPnAgdh9GtNcbWW07LBFCloqrHDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T04:43:34.673199Z"},"content_sha256":"bd6f3b6ff2a0f3461b4e5e6c40c9bb648bd8b9db85faa3033a9af90ca19ac901","schema_version":"1.0","event_id":"sha256:bd6f3b6ff2a0f3461b4e5e6c40c9bb648bd8b9db85faa3033a9af90ca19ac901"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:GQ332FR665PAYXFOU3HA5ONDUC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Joint Detection and Identification Feature Learning for Person Search","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bochao Wang, Liang Lin, Shuang Li, Tong Xiao, Xiaogang Wang","submitted_at":"2016-04-07T02:16:26Z","abstract_excerpt":"Existing person re-identification benchmarks and methods mainly focus on matching cropped pedestrian images between queries and candidates. However, it is different from real-world scenarios where the annotations of pedestrian bounding boxes are unavailable and the target person needs to be searched from a gallery of whole scene images. To close the gap, we propose a new deep learning framework for person search. Instead of breaking it down into two separate tasks---pedestrian detection and person re-identification, we jointly handle both aspects in a single convolutional neural network. An On"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.01850","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":""},"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":"2026-05-18T00:46:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZphAiytohxx/X8n64MEEVuK++wEs2fyB44ySY5SqOJIkrjrIJrv+NJgrUrU/gPa6GBsl9pHtl2wNyEwhbEmeDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T04:43:34.673849Z"},"content_sha256":"eb404742c7820821c949f674694c6dc5018a013b663ba0733ef45c2ed254cf1a","schema_version":"1.0","event_id":"sha256:eb404742c7820821c949f674694c6dc5018a013b663ba0733ef45c2ed254cf1a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GQ332FR665PAYXFOU3HA5ONDUC/bundle.json","state_url":"https://pith.science/pith/GQ332FR665PAYXFOU3HA5ONDUC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GQ332FR665PAYXFOU3HA5ONDUC/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":"2026-05-27T04:43:34Z","links":{"resolver":"https://pith.science/pith/GQ332FR665PAYXFOU3HA5ONDUC","bundle":"https://pith.science/pith/GQ332FR665PAYXFOU3HA5ONDUC/bundle.json","state":"https://pith.science/pith/GQ332FR665PAYXFOU3HA5ONDUC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GQ332FR665PAYXFOU3HA5ONDUC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:GQ332FR665PAYXFOU3HA5ONDUC","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":"de2d27ca7542b07fb9cb5d65917d8977bfd769d0d097140aaa4741e250fd514e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2016-04-07T02:16:26Z","title_canon_sha256":"2a6f9c09eaad91e0afcc1e80470ea8f71085f41c6f586960be24d763b07145f1"},"schema_version":"1.0","source":{"id":"1604.01850","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.01850","created_at":"2026-05-18T00:46:55Z"},{"alias_kind":"arxiv_version","alias_value":"1604.01850v3","created_at":"2026-05-18T00:46:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.01850","created_at":"2026-05-18T00:46:55Z"},{"alias_kind":"pith_short_12","alias_value":"GQ332FR665PA","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_16","alias_value":"GQ332FR665PAYXFO","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_8","alias_value":"GQ332FR6","created_at":"2026-05-18T12:30:19Z"}],"graph_snapshots":[{"event_id":"sha256:eb404742c7820821c949f674694c6dc5018a013b663ba0733ef45c2ed254cf1a","target":"graph","created_at":"2026-05-18T00:46:55Z","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":"Existing person re-identification benchmarks and methods mainly focus on matching cropped pedestrian images between queries and candidates. However, it is different from real-world scenarios where the annotations of pedestrian bounding boxes are unavailable and the target person needs to be searched from a gallery of whole scene images. To close the gap, we propose a new deep learning framework for person search. Instead of breaking it down into two separate tasks---pedestrian detection and person re-identification, we jointly handle both aspects in a single convolutional neural network. An On","authors_text":"Bochao Wang, Liang Lin, Shuang Li, Tong Xiao, Xiaogang Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2016-04-07T02:16:26Z","title":"Joint Detection and Identification Feature Learning for Person Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.01850","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:bd6f3b6ff2a0f3461b4e5e6c40c9bb648bd8b9db85faa3033a9af90ca19ac901","target":"record","created_at":"2026-05-18T00:46:55Z","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":"de2d27ca7542b07fb9cb5d65917d8977bfd769d0d097140aaa4741e250fd514e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2016-04-07T02:16:26Z","title_canon_sha256":"2a6f9c09eaad91e0afcc1e80470ea8f71085f41c6f586960be24d763b07145f1"},"schema_version":"1.0","source":{"id":"1604.01850","kind":"arxiv","version":3}},"canonical_sha256":"3437bd163ef75e0c5caea6ce0eb9a3a09d9f8205be1becf2c5e33bbd420fffff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3437bd163ef75e0c5caea6ce0eb9a3a09d9f8205be1becf2c5e33bbd420fffff","first_computed_at":"2026-05-18T00:46:55.766152Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:46:55.766152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"x0lE7lXDzMranfEYrXGXAcl+dN3QWoN6MKmyn2jamYLqEM+fezyPm08TpE0qFokJuut6Y/qL0cqeUI1Co8RCDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:46:55.766572Z","signed_message":"canonical_sha256_bytes"},"source_id":"1604.01850","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bd6f3b6ff2a0f3461b4e5e6c40c9bb648bd8b9db85faa3033a9af90ca19ac901","sha256:eb404742c7820821c949f674694c6dc5018a013b663ba0733ef45c2ed254cf1a"],"state_sha256":"6c1b035e834b49c9375caab141f007b36f90cc05ca395619a203bb04c8bcc23b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QMgPijgwlYf9DiK8WKaEpuXlrupqxTxoGjOpmpvd91FFHa4Q/ulOH8zJgUsPI+QYqqK34cJeBN/mCPZacu5TAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T04:43:34.677248Z","bundle_sha256":"1a1d709a35d9b7e2505c2e3df0dc42d59bffa934ee4a09dad5be9dca6012005b"}}