{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:UH3Y6BJDQC4HAY6XYNBGXFHAAF","short_pith_number":"pith:UH3Y6BJD","canonical_record":{"source":{"id":"1711.09349","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2017-11-26T08:44:53Z","cross_cats_sorted":[],"title_canon_sha256":"2872fc43ecf44b73983c5b7223f6ed4049ef340e743f19bb564a0b3ecedcb7f6","abstract_canon_sha256":"6df4aae9cb03ab29e7aa2d8e21fb20b702585676ae979f461e6229322097193b"},"schema_version":"1.0"},"canonical_sha256":"a1f78f052380b87063d7c3426b94e0017a4282cca97f7c559b22cb2cb5315198","source":{"kind":"arxiv","id":"1711.09349","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.09349","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"arxiv_version","alias_value":"1711.09349v3","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.09349","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"pith_short_12","alias_value":"UH3Y6BJDQC4H","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"UH3Y6BJDQC4HAY6X","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"UH3Y6BJD","created_at":"2026-05-18T12:31:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:UH3Y6BJDQC4HAY6XYNBGXFHAAF","target":"record","payload":{"canonical_record":{"source":{"id":"1711.09349","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2017-11-26T08:44:53Z","cross_cats_sorted":[],"title_canon_sha256":"2872fc43ecf44b73983c5b7223f6ed4049ef340e743f19bb564a0b3ecedcb7f6","abstract_canon_sha256":"6df4aae9cb03ab29e7aa2d8e21fb20b702585676ae979f461e6229322097193b"},"schema_version":"1.0"},"canonical_sha256":"a1f78f052380b87063d7c3426b94e0017a4282cca97f7c559b22cb2cb5315198","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:26:23.645211Z","signature_b64":"n4HMxuQ5lO2lsmNt4HZG/Rb8gSdN747lv5veSyeoOkUtOXIWY2skjYCIJdjXuxpgvPuuAbLj3b6avualULe6AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a1f78f052380b87063d7c3426b94e0017a4282cca97f7c559b22cb2cb5315198","last_reissued_at":"2026-05-18T00:26:23.644490Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:26:23.644490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.09349","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":"2026-05-18T00:26:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uZA2idn7hOouJ17KGuVdxb+eQZYP3fbMWmCmPoqQ+En73eDpwaSxV2sXkgpp4ydg2Rn6gHmEhx/x0If6gXfCDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T02:26:51.294481Z"},"content_sha256":"45b3fb37bd2544322cc3d443f6b1357d492d7076ef0a55d7fced8235496ae999","schema_version":"1.0","event_id":"sha256:45b3fb37bd2544322cc3d443f6b1357d492d7076ef0a55d7fced8235496ae999"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:UH3Y6BJDQC4HAY6XYNBGXFHAAF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Liang Zheng, Qi Tian, Shengjin Wang, Yifan Sun, Yi Yang","submitted_at":"2017-11-26T08:44:53Z","abstract_excerpt":"Employing part-level features for pedestrian image description offers fine-grained information and has been verified as beneficial for person retrieval in very recent literature. A prerequisite of part discovery is that each part should be well located. Instead of using external cues, e.g., pose estimation, to directly locate parts, this paper lays emphasis on the content consistency within each part.\n  Specifically, we target at learning discriminative part-informed features for person retrieval and make two contributions. (i) A network named Part-based Convolutional Baseline (PCB). Given an "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.09349","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":"2026-05-18T00:26:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"avqo0xH9Q5ITzOsyTXA0SFA3FkmGTZuf+sClZAv0LoQFshknVYA420eSd1iQj3RjFRxNLgsjHhN7Ptw9mASMAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T02:26:51.294894Z"},"content_sha256":"a88706ebe4a5382e752185be2ec2e0144016e9d4150cdf5974d6c09d47811231","schema_version":"1.0","event_id":"sha256:a88706ebe4a5382e752185be2ec2e0144016e9d4150cdf5974d6c09d47811231"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UH3Y6BJDQC4HAY6XYNBGXFHAAF/bundle.json","state_url":"https://pith.science/pith/UH3Y6BJDQC4HAY6XYNBGXFHAAF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UH3Y6BJDQC4HAY6XYNBGXFHAAF/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":"2026-05-30T02:26:51Z","links":{"resolver":"https://pith.science/pith/UH3Y6BJDQC4HAY6XYNBGXFHAAF","bundle":"https://pith.science/pith/UH3Y6BJDQC4HAY6XYNBGXFHAAF/bundle.json","state":"https://pith.science/pith/UH3Y6BJDQC4HAY6XYNBGXFHAAF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UH3Y6BJDQC4HAY6XYNBGXFHAAF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:UH3Y6BJDQC4HAY6XYNBGXFHAAF","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":"6df4aae9cb03ab29e7aa2d8e21fb20b702585676ae979f461e6229322097193b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2017-11-26T08:44:53Z","title_canon_sha256":"2872fc43ecf44b73983c5b7223f6ed4049ef340e743f19bb564a0b3ecedcb7f6"},"schema_version":"1.0","source":{"id":"1711.09349","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.09349","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"arxiv_version","alias_value":"1711.09349v3","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.09349","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"pith_short_12","alias_value":"UH3Y6BJDQC4H","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"UH3Y6BJDQC4HAY6X","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"UH3Y6BJD","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:a88706ebe4a5382e752185be2ec2e0144016e9d4150cdf5974d6c09d47811231","target":"graph","created_at":"2026-05-18T00:26:23Z","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":"Employing part-level features for pedestrian image description offers fine-grained information and has been verified as beneficial for person retrieval in very recent literature. A prerequisite of part discovery is that each part should be well located. Instead of using external cues, e.g., pose estimation, to directly locate parts, this paper lays emphasis on the content consistency within each part.\n  Specifically, we target at learning discriminative part-informed features for person retrieval and make two contributions. (i) A network named Part-based Convolutional Baseline (PCB). Given an ","authors_text":"Liang Zheng, Qi Tian, Shengjin Wang, Yifan Sun, Yi Yang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2017-11-26T08:44:53Z","title":"Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.09349","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":"sha256:45b3fb37bd2544322cc3d443f6b1357d492d7076ef0a55d7fced8235496ae999","target":"record","created_at":"2026-05-18T00:26:23Z","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":"6df4aae9cb03ab29e7aa2d8e21fb20b702585676ae979f461e6229322097193b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2017-11-26T08:44:53Z","title_canon_sha256":"2872fc43ecf44b73983c5b7223f6ed4049ef340e743f19bb564a0b3ecedcb7f6"},"schema_version":"1.0","source":{"id":"1711.09349","kind":"arxiv","version":3}},"canonical_sha256":"a1f78f052380b87063d7c3426b94e0017a4282cca97f7c559b22cb2cb5315198","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a1f78f052380b87063d7c3426b94e0017a4282cca97f7c559b22cb2cb5315198","first_computed_at":"2026-05-18T00:26:23.644490Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:26:23.644490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"n4HMxuQ5lO2lsmNt4HZG/Rb8gSdN747lv5veSyeoOkUtOXIWY2skjYCIJdjXuxpgvPuuAbLj3b6avualULe6AQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:26:23.645211Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.09349","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:45b3fb37bd2544322cc3d443f6b1357d492d7076ef0a55d7fced8235496ae999","sha256:a88706ebe4a5382e752185be2ec2e0144016e9d4150cdf5974d6c09d47811231"],"state_sha256":"523b182ffff797b77dbba3d1a990ce8b5bfa8bd3d335bce29cbc7e6147b2f181"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bQ5xZ6H3uu7pL0znZrMGKANCQwBmR4K5Yzv1KiJF/4KZ7+AkPWi6vrWo+sVoZ4i/lyOiuMLemCDfy1m7BpAwDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T02:26:51.297712Z","bundle_sha256":"15a3162778dba2d180525137c9cc8f2360f1d57214458e1ca836b8c419571a05"}}