{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LIEPZXLUDUIKRYBQFFPAOYB26N","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":"e97345063950b368bac7e81ed8451e4a9aabadf2f8cb90beece88c173ffffba4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-19T03:33:51Z","title_canon_sha256":"a899ca2b1d851051e2e81d9a05c572a4c4a8e603d0862b5435088f81a3e66956"},"schema_version":"1.0","source":{"id":"1707.05929","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.05929","created_at":"2026-05-18T00:38:01Z"},{"alias_kind":"arxiv_version","alias_value":"1707.05929v2","created_at":"2026-05-18T00:38:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.05929","created_at":"2026-05-18T00:38:01Z"},{"alias_kind":"pith_short_12","alias_value":"LIEPZXLUDUIK","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LIEPZXLUDUIKRYBQ","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LIEPZXLU","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:b710d5e7431639cb57c9c427e540f6a4bbb4a9a217371801878ed159f6f63c24","target":"graph","created_at":"2026-05-18T00:38:01Z","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":"In apparel recognition, specialized models (e.g. models trained for a particular vertical like dresses) can significantly outperform general models (i.e. models that cover a wide range of verticals). Therefore, deep neural network models are often trained separately for different verticals. However, using specialized models for different verticals is not scalable and expensive to deploy. This paper addresses the problem of learning one unified embedding model for multiple object verticals (e.g. all apparel classes) without sacrificing accuracy. The problem is tackled from two aspects: training","authors_text":"Bo Wu, Chao-Yeh Chen, Hartwig Adam, Xiao Zhang, Yang Song, Yuan Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-19T03:33:51Z","title":"Learning Unified Embedding for Apparel Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.05929","kind":"arxiv","version":2},"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:e17dc7d62210b67a519ee701719eaec502d250d9fe775aa42131c3774c590d58","target":"record","created_at":"2026-05-18T00:38:01Z","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":"e97345063950b368bac7e81ed8451e4a9aabadf2f8cb90beece88c173ffffba4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-19T03:33:51Z","title_canon_sha256":"a899ca2b1d851051e2e81d9a05c572a4c4a8e603d0862b5435088f81a3e66956"},"schema_version":"1.0","source":{"id":"1707.05929","kind":"arxiv","version":2}},"canonical_sha256":"5a08fcdd741d10a8e030295e07603af34d93383d28fab9fac3fb7f6b60940e2d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a08fcdd741d10a8e030295e07603af34d93383d28fab9fac3fb7f6b60940e2d","first_computed_at":"2026-05-18T00:38:01.707056Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:38:01.707056Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0KOErI+2WLKhE3CCfKIfIBDMbI4u23y0LB/O5OrKvzpBQ7qDdlTLn85sSSE2rZFW73oULMnGHAoONtlk62OPCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:38:01.707617Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.05929","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e17dc7d62210b67a519ee701719eaec502d250d9fe775aa42131c3774c590d58","sha256:b710d5e7431639cb57c9c427e540f6a4bbb4a9a217371801878ed159f6f63c24"],"state_sha256":"9839288aa8daa2ed2841fb271038fb8be079d4a7318a02f55ad134ae0dc3bd12"}