{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:JRODF7YWXDGZQ6JIR77LUHKILF","short_pith_number":"pith:JRODF7YW","schema_version":"1.0","canonical_sha256":"4c5c32ff16b8cd9879288ffeba1d48595b27f1ba39d48612fb339fa1bc609f67","source":{"kind":"arxiv","id":"1807.01459","version":2},"attestation_state":"computed","paper":{"title":"Deep Saliency Hashing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hongxun Yao, Lei Zhang, Shangchen Zhou, Sheng Jin, Xiansheng Hua, Xiaoshuai Sun","submitted_at":"2018-07-04T06:31:13Z","abstract_excerpt":"In recent years, hashing methods have been proved to be effective and efficient for the large-scale Web media search. However, the existing general hashing methods have limited discriminative power for describing fine-grained objects that share similar overall appearance but have subtle difference. To solve this problem, we for the first time introduce the attention mechanism to the learning of fine-grained hashing codes. Specifically, we propose a novel deep hashing model, named deep saliency hashing (DSaH), which automatically mines salient regions and learns semantic-preserving hashing code"},"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":"1807.01459","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-04T06:31:13Z","cross_cats_sorted":[],"title_canon_sha256":"e4bd0a72ea45babccd77394f718ffc77fc96ec27ca37c476b991118dbd94b0f1","abstract_canon_sha256":"26571bfa6f6d376a981e5de22cae0df4a7653f636e64877d8a0d5458df4409c0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:59.086270Z","signature_b64":"T6l6LrZkk83TfJv6/cmf+4CY+RgfuPO5tm00qi9dqTnemnChna6n0H37kj3CogNniwKzCL1C/75M6UcMyGblDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4c5c32ff16b8cd9879288ffeba1d48595b27f1ba39d48612fb339fa1bc609f67","last_reissued_at":"2026-05-17T23:54:59.085761Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:59.085761Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Deep Saliency Hashing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hongxun Yao, Lei Zhang, Shangchen Zhou, Sheng Jin, Xiansheng Hua, Xiaoshuai Sun","submitted_at":"2018-07-04T06:31:13Z","abstract_excerpt":"In recent years, hashing methods have been proved to be effective and efficient for the large-scale Web media search. However, the existing general hashing methods have limited discriminative power for describing fine-grained objects that share similar overall appearance but have subtle difference. To solve this problem, we for the first time introduce the attention mechanism to the learning of fine-grained hashing codes. Specifically, we propose a novel deep hashing model, named deep saliency hashing (DSaH), which automatically mines salient regions and learns semantic-preserving hashing code"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.01459","kind":"arxiv","version":2},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1807.01459","created_at":"2026-05-17T23:54:59.085865+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.01459v2","created_at":"2026-05-17T23:54:59.085865+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.01459","created_at":"2026-05-17T23:54:59.085865+00:00"},{"alias_kind":"pith_short_12","alias_value":"JRODF7YWXDGZ","created_at":"2026-05-18T12:32:31.084164+00:00"},{"alias_kind":"pith_short_16","alias_value":"JRODF7YWXDGZQ6JI","created_at":"2026-05-18T12:32:31.084164+00:00"},{"alias_kind":"pith_short_8","alias_value":"JRODF7YW","created_at":"2026-05-18T12:32:31.084164+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/JRODF7YWXDGZQ6JIR77LUHKILF","json":"https://pith.science/pith/JRODF7YWXDGZQ6JIR77LUHKILF.json","graph_json":"https://pith.science/api/pith-number/JRODF7YWXDGZQ6JIR77LUHKILF/graph.json","events_json":"https://pith.science/api/pith-number/JRODF7YWXDGZQ6JIR77LUHKILF/events.json","paper":"https://pith.science/paper/JRODF7YW"},"agent_actions":{"view_html":"https://pith.science/pith/JRODF7YWXDGZQ6JIR77LUHKILF","download_json":"https://pith.science/pith/JRODF7YWXDGZQ6JIR77LUHKILF.json","view_paper":"https://pith.science/paper/JRODF7YW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.01459&json=true","fetch_graph":"https://pith.science/api/pith-number/JRODF7YWXDGZQ6JIR77LUHKILF/graph.json","fetch_events":"https://pith.science/api/pith-number/JRODF7YWXDGZQ6JIR77LUHKILF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JRODF7YWXDGZQ6JIR77LUHKILF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JRODF7YWXDGZQ6JIR77LUHKILF/action/storage_attestation","attest_author":"https://pith.science/pith/JRODF7YWXDGZQ6JIR77LUHKILF/action/author_attestation","sign_citation":"https://pith.science/pith/JRODF7YWXDGZQ6JIR77LUHKILF/action/citation_signature","submit_replication":"https://pith.science/pith/JRODF7YWXDGZQ6JIR77LUHKILF/action/replication_record"}},"created_at":"2026-05-17T23:54:59.085865+00:00","updated_at":"2026-05-17T23:54:59.085865+00:00"}