{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:VHZEGK22VY4YDHZDOQ6A4PSOCA","short_pith_number":"pith:VHZEGK22","schema_version":"1.0","canonical_sha256":"a9f2432b5aae39819f23743c0e3e4e1025d1196648de2c75aeeffeef9d5166a7","source":{"kind":"arxiv","id":"2407.03632","version":1},"attestation_state":"computed","paper":{"title":"CLASH: Complementary Learning with Neural Architecture Search for Gait Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huanzhang Dou, Lu Jin, Pengyi Zhang, Xi Li, Yuhan Zhao","submitted_at":"2024-07-04T04:51:01Z","abstract_excerpt":"Gait recognition, which aims at identifying individuals by their walking patterns, has achieved great success based on silhouette. The binary silhouette sequence encodes the walking pattern within the sparse boundary representation. Therefore, most pixels in the silhouette are under-sensitive to the walking pattern since the sparse boundary lacks dense spatial-temporal information, which is suitable to be represented with dense texture. To enhance the sensitivity to the walking pattern while maintaining the robustness of recognition, we present a Complementary Learning with neural Architecture"},"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":"2407.03632","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-04T04:51:01Z","cross_cats_sorted":[],"title_canon_sha256":"320ca3d31145058c796c3b3e7ec4c8f6b350e5fd4b7a62616bb4c047b85e3acd","abstract_canon_sha256":"aa5efa589f85c5bd666dbea1928f812fbd86daa05e8afee8d7c7b1444610e730"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:40:21.084152Z","signature_b64":"Kf0awLXIOLdr7VAvLTfGYbwaRkXXiPoQNvbeOHzaP+5s4M0dAeLWpIZ8zr14d7SFY+Z25WQYoAUF6fOoW1HBDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a9f2432b5aae39819f23743c0e3e4e1025d1196648de2c75aeeffeef9d5166a7","last_reissued_at":"2026-07-05T08:40:21.083638Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:40:21.083638Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CLASH: Complementary Learning with Neural Architecture Search for Gait Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huanzhang Dou, Lu Jin, Pengyi Zhang, Xi Li, Yuhan Zhao","submitted_at":"2024-07-04T04:51:01Z","abstract_excerpt":"Gait recognition, which aims at identifying individuals by their walking patterns, has achieved great success based on silhouette. The binary silhouette sequence encodes the walking pattern within the sparse boundary representation. Therefore, most pixels in the silhouette are under-sensitive to the walking pattern since the sparse boundary lacks dense spatial-temporal information, which is suitable to be represented with dense texture. To enhance the sensitivity to the walking pattern while maintaining the robustness of recognition, we present a Complementary Learning with neural Architecture"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.03632","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/2407.03632/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":"2407.03632","created_at":"2026-07-05T08:40:21.083698+00:00"},{"alias_kind":"arxiv_version","alias_value":"2407.03632v1","created_at":"2026-07-05T08:40:21.083698+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.03632","created_at":"2026-07-05T08:40:21.083698+00:00"},{"alias_kind":"pith_short_12","alias_value":"VHZEGK22VY4Y","created_at":"2026-07-05T08:40:21.083698+00:00"},{"alias_kind":"pith_short_16","alias_value":"VHZEGK22VY4YDHZD","created_at":"2026-07-05T08:40:21.083698+00:00"},{"alias_kind":"pith_short_8","alias_value":"VHZEGK22","created_at":"2026-07-05T08:40:21.083698+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/VHZEGK22VY4YDHZDOQ6A4PSOCA","json":"https://pith.science/pith/VHZEGK22VY4YDHZDOQ6A4PSOCA.json","graph_json":"https://pith.science/api/pith-number/VHZEGK22VY4YDHZDOQ6A4PSOCA/graph.json","events_json":"https://pith.science/api/pith-number/VHZEGK22VY4YDHZDOQ6A4PSOCA/events.json","paper":"https://pith.science/paper/VHZEGK22"},"agent_actions":{"view_html":"https://pith.science/pith/VHZEGK22VY4YDHZDOQ6A4PSOCA","download_json":"https://pith.science/pith/VHZEGK22VY4YDHZDOQ6A4PSOCA.json","view_paper":"https://pith.science/paper/VHZEGK22","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2407.03632&json=true","fetch_graph":"https://pith.science/api/pith-number/VHZEGK22VY4YDHZDOQ6A4PSOCA/graph.json","fetch_events":"https://pith.science/api/pith-number/VHZEGK22VY4YDHZDOQ6A4PSOCA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VHZEGK22VY4YDHZDOQ6A4PSOCA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VHZEGK22VY4YDHZDOQ6A4PSOCA/action/storage_attestation","attest_author":"https://pith.science/pith/VHZEGK22VY4YDHZDOQ6A4PSOCA/action/author_attestation","sign_citation":"https://pith.science/pith/VHZEGK22VY4YDHZDOQ6A4PSOCA/action/citation_signature","submit_replication":"https://pith.science/pith/VHZEGK22VY4YDHZDOQ6A4PSOCA/action/replication_record"}},"created_at":"2026-07-05T08:40:21.083698+00:00","updated_at":"2026-07-05T08:40:21.083698+00:00"}