{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:YPD4PFJEHZFC7XTWC2DZEJIPGP","short_pith_number":"pith:YPD4PFJE","schema_version":"1.0","canonical_sha256":"c3c7c795243e4a2fde76168792250f33d5d590c032b961a7587e6ca6e8cfb868","source":{"kind":"arxiv","id":"1511.05296","version":2},"attestation_state":"computed","paper":{"title":"Towards Predicting the Likeability of Fashion Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abrar Abdul Nabi, Chengde Wan, Gang Wang, Jinghua Wang, Tian-Tsong Ng","submitted_at":"2015-11-17T07:31:36Z","abstract_excerpt":"In this paper, we propose a method for ranking fashion images to find the ones which might be liked by more people. We collect two new datasets from image sharing websites (Pinterest and Polyvore). We represent fashion images based on attributes: semantic attributes and data-driven attributes. To learn semantic attributes from limited training data, we use an algorithm on multi-task convolutional neural networks to share visual knowledge among different semantic attribute categories. To discover data-driven attributes unsupervisedly, we propose an algorithm to simultaneously discover visual cl"},"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":"1511.05296","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-17T07:31:36Z","cross_cats_sorted":[],"title_canon_sha256":"aaef100a7c13b303a96bf6470fd59690fde8e14ae2b3b3dacdbe9f06e3fc6037","abstract_canon_sha256":"cf44a7015e830d27447c3b66c05c50962b170b95052923ad2ad2d43349df747d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:26:17.505359Z","signature_b64":"WADwGHP/ernyKsuAAuSXvJsX+TnhPkp4rSqb1lEN6xLlBqWuOc3+wT3Gr27PrxJfvpwQ29Qrd3C39xS7r5QlAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c3c7c795243e4a2fde76168792250f33d5d590c032b961a7587e6ca6e8cfb868","last_reissued_at":"2026-05-18T01:26:17.504782Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:26:17.504782Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards Predicting the Likeability of Fashion Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abrar Abdul Nabi, Chengde Wan, Gang Wang, Jinghua Wang, Tian-Tsong Ng","submitted_at":"2015-11-17T07:31:36Z","abstract_excerpt":"In this paper, we propose a method for ranking fashion images to find the ones which might be liked by more people. We collect two new datasets from image sharing websites (Pinterest and Polyvore). We represent fashion images based on attributes: semantic attributes and data-driven attributes. To learn semantic attributes from limited training data, we use an algorithm on multi-task convolutional neural networks to share visual knowledge among different semantic attribute categories. To discover data-driven attributes unsupervisedly, we propose an algorithm to simultaneously discover visual cl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.05296","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":"1511.05296","created_at":"2026-05-18T01:26:17.504886+00:00"},{"alias_kind":"arxiv_version","alias_value":"1511.05296v2","created_at":"2026-05-18T01:26:17.504886+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.05296","created_at":"2026-05-18T01:26:17.504886+00:00"},{"alias_kind":"pith_short_12","alias_value":"YPD4PFJEHZFC","created_at":"2026-05-18T12:29:50.041715+00:00"},{"alias_kind":"pith_short_16","alias_value":"YPD4PFJEHZFC7XTW","created_at":"2026-05-18T12:29:50.041715+00:00"},{"alias_kind":"pith_short_8","alias_value":"YPD4PFJE","created_at":"2026-05-18T12:29:50.041715+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/YPD4PFJEHZFC7XTWC2DZEJIPGP","json":"https://pith.science/pith/YPD4PFJEHZFC7XTWC2DZEJIPGP.json","graph_json":"https://pith.science/api/pith-number/YPD4PFJEHZFC7XTWC2DZEJIPGP/graph.json","events_json":"https://pith.science/api/pith-number/YPD4PFJEHZFC7XTWC2DZEJIPGP/events.json","paper":"https://pith.science/paper/YPD4PFJE"},"agent_actions":{"view_html":"https://pith.science/pith/YPD4PFJEHZFC7XTWC2DZEJIPGP","download_json":"https://pith.science/pith/YPD4PFJEHZFC7XTWC2DZEJIPGP.json","view_paper":"https://pith.science/paper/YPD4PFJE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1511.05296&json=true","fetch_graph":"https://pith.science/api/pith-number/YPD4PFJEHZFC7XTWC2DZEJIPGP/graph.json","fetch_events":"https://pith.science/api/pith-number/YPD4PFJEHZFC7XTWC2DZEJIPGP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YPD4PFJEHZFC7XTWC2DZEJIPGP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YPD4PFJEHZFC7XTWC2DZEJIPGP/action/storage_attestation","attest_author":"https://pith.science/pith/YPD4PFJEHZFC7XTWC2DZEJIPGP/action/author_attestation","sign_citation":"https://pith.science/pith/YPD4PFJEHZFC7XTWC2DZEJIPGP/action/citation_signature","submit_replication":"https://pith.science/pith/YPD4PFJEHZFC7XTWC2DZEJIPGP/action/replication_record"}},"created_at":"2026-05-18T01:26:17.504886+00:00","updated_at":"2026-05-18T01:26:17.504886+00:00"}