{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:WENXEXORDRBZWBFDPJU6YY3NMW","short_pith_number":"pith:WENXEXOR","schema_version":"1.0","canonical_sha256":"b11b725dd11c439b04a37a69ec636d659cd8a0d27d8fec9a08844347381c18ba","source":{"kind":"arxiv","id":"2110.11264","version":1},"attestation_state":"computed","paper":{"title":"MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Congyan Lang, Tengfei Liang, Wu Liu, Xiaoyan Gu, Yajun Gao, Yidong Li, Yi Jin","submitted_at":"2021-10-21T16:45:23Z","abstract_excerpt":"The RGB-infrared cross-modality person re-identification (ReID) task aims to recognize the images of the same identity between the visible modality and the infrared modality. Existing methods mainly use a two-stream architecture to eliminate the discrepancy between the two modalities in the final common feature space, which ignore the single space of each modality in the shallow layers. To solve it, in this paper, we present a novel multi-feature space joint optimization (MSO) network, which can learn modality-sharable features in both the single-modality space and the common space. Firstly, b"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2110.11264","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-21T16:45:23Z","cross_cats_sorted":[],"title_canon_sha256":"7762309a243c5686cf55f4635dd6c9486917348343c50f28a6b2459d83d35078","abstract_canon_sha256":"6a042b835092d4757d556d6e96bb9dd8f9dd920505350799dcba8adc32714bc4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:24:37.933954Z","signature_b64":"Kv76CRWdahWS71ThCscQak4UAVxxh7xww8AcVaYAuu2MfMZNcLk3jutVxAWPMi9VZOP7JvArcEbHVYV9ktA3Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b11b725dd11c439b04a37a69ec636d659cd8a0d27d8fec9a08844347381c18ba","last_reissued_at":"2026-07-05T03:24:37.933490Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:24:37.933490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Congyan Lang, Tengfei Liang, Wu Liu, Xiaoyan Gu, Yajun Gao, Yidong Li, Yi Jin","submitted_at":"2021-10-21T16:45:23Z","abstract_excerpt":"The RGB-infrared cross-modality person re-identification (ReID) task aims to recognize the images of the same identity between the visible modality and the infrared modality. Existing methods mainly use a two-stream architecture to eliminate the discrepancy between the two modalities in the final common feature space, which ignore the single space of each modality in the shallow layers. To solve it, in this paper, we present a novel multi-feature space joint optimization (MSO) network, which can learn modality-sharable features in both the single-modality space and the common space. Firstly, b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.11264","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/2110.11264/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2110.11264","created_at":"2026-07-05T03:24:37.933550+00:00"},{"alias_kind":"arxiv_version","alias_value":"2110.11264v1","created_at":"2026-07-05T03:24:37.933550+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.11264","created_at":"2026-07-05T03:24:37.933550+00:00"},{"alias_kind":"pith_short_12","alias_value":"WENXEXORDRBZ","created_at":"2026-07-05T03:24:37.933550+00:00"},{"alias_kind":"pith_short_16","alias_value":"WENXEXORDRBZWBFD","created_at":"2026-07-05T03:24:37.933550+00:00"},{"alias_kind":"pith_short_8","alias_value":"WENXEXOR","created_at":"2026-07-05T03:24:37.933550+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WENXEXORDRBZWBFDPJU6YY3NMW","json":"https://pith.science/pith/WENXEXORDRBZWBFDPJU6YY3NMW.json","graph_json":"https://pith.science/api/pith-number/WENXEXORDRBZWBFDPJU6YY3NMW/graph.json","events_json":"https://pith.science/api/pith-number/WENXEXORDRBZWBFDPJU6YY3NMW/events.json","paper":"https://pith.science/paper/WENXEXOR"},"agent_actions":{"view_html":"https://pith.science/pith/WENXEXORDRBZWBFDPJU6YY3NMW","download_json":"https://pith.science/pith/WENXEXORDRBZWBFDPJU6YY3NMW.json","view_paper":"https://pith.science/paper/WENXEXOR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2110.11264&json=true","fetch_graph":"https://pith.science/api/pith-number/WENXEXORDRBZWBFDPJU6YY3NMW/graph.json","fetch_events":"https://pith.science/api/pith-number/WENXEXORDRBZWBFDPJU6YY3NMW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WENXEXORDRBZWBFDPJU6YY3NMW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WENXEXORDRBZWBFDPJU6YY3NMW/action/storage_attestation","attest_author":"https://pith.science/pith/WENXEXORDRBZWBFDPJU6YY3NMW/action/author_attestation","sign_citation":"https://pith.science/pith/WENXEXORDRBZWBFDPJU6YY3NMW/action/citation_signature","submit_replication":"https://pith.science/pith/WENXEXORDRBZWBFDPJU6YY3NMW/action/replication_record"}},"created_at":"2026-07-05T03:24:37.933550+00:00","updated_at":"2026-07-05T03:24:37.933550+00:00"}