{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:GCZXUIRCVWZU54XCEKAXVS3VZS","short_pith_number":"pith:GCZXUIRC","schema_version":"1.0","canonical_sha256":"30b37a2222adb34ef2e222817acb75ccb83ece3167ec91f589a3e548f1de58c6","source":{"kind":"arxiv","id":"1407.2987","version":1},"attestation_state":"computed","paper":{"title":"FAME: Face Association through Model Evolution","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","headline":"","cross_cats":["cs.AI","cs.IR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Eren Golge, Pinar Duygulu","submitted_at":"2014-07-10T23:52:44Z","abstract_excerpt":"We attack the problem of learning face models for public faces from weakly-labelled images collected from web through querying a name. The data is very noisy even after face detection, with several irrelevant faces corresponding to other people. We propose a novel method, Face Association through Model Evolution (FAME), that is able to prune the data in an iterative way, for the face models associated to a name to evolve. The idea is based on capturing discriminativeness and representativeness of each instance and eliminating the outliers. The final models are used to classify faces on novel d"},"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":"1407.2987","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","primary_cat":"cs.CV","submitted_at":"2014-07-10T23:52:44Z","cross_cats_sorted":["cs.AI","cs.IR","cs.LG"],"title_canon_sha256":"f2897b18e5bfdc88a9517bf0ff1f23db669cfa2e4964c5980bf4a00c838e74ff","abstract_canon_sha256":"4353dfc3a4a1df80b9286cda8343fcddee02a27f562a4ac3aab8d9091aecaf7c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:47:52.301978Z","signature_b64":"r0EBdbMReyMtkV1J6IQwL9+yr8MEyURdeIbJ+wq+SId3U6HrGrmDd2eaR13qBjQRq01l1M7emO+DLLr54IQEDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"30b37a2222adb34ef2e222817acb75ccb83ece3167ec91f589a3e548f1de58c6","last_reissued_at":"2026-05-18T02:47:52.301472Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:47:52.301472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FAME: Face Association through Model Evolution","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","headline":"","cross_cats":["cs.AI","cs.IR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Eren Golge, Pinar Duygulu","submitted_at":"2014-07-10T23:52:44Z","abstract_excerpt":"We attack the problem of learning face models for public faces from weakly-labelled images collected from web through querying a name. The data is very noisy even after face detection, with several irrelevant faces corresponding to other people. We propose a novel method, Face Association through Model Evolution (FAME), that is able to prune the data in an iterative way, for the face models associated to a name to evolve. The idea is based on capturing discriminativeness and representativeness of each instance and eliminating the outliers. The final models are used to classify faces on novel d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.2987","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":""},"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":"1407.2987","created_at":"2026-05-18T02:47:52.301563+00:00"},{"alias_kind":"arxiv_version","alias_value":"1407.2987v1","created_at":"2026-05-18T02:47:52.301563+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.2987","created_at":"2026-05-18T02:47:52.301563+00:00"},{"alias_kind":"pith_short_12","alias_value":"GCZXUIRCVWZU","created_at":"2026-05-18T12:28:30.664211+00:00"},{"alias_kind":"pith_short_16","alias_value":"GCZXUIRCVWZU54XC","created_at":"2026-05-18T12:28:30.664211+00:00"},{"alias_kind":"pith_short_8","alias_value":"GCZXUIRC","created_at":"2026-05-18T12:28:30.664211+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/GCZXUIRCVWZU54XCEKAXVS3VZS","json":"https://pith.science/pith/GCZXUIRCVWZU54XCEKAXVS3VZS.json","graph_json":"https://pith.science/api/pith-number/GCZXUIRCVWZU54XCEKAXVS3VZS/graph.json","events_json":"https://pith.science/api/pith-number/GCZXUIRCVWZU54XCEKAXVS3VZS/events.json","paper":"https://pith.science/paper/GCZXUIRC"},"agent_actions":{"view_html":"https://pith.science/pith/GCZXUIRCVWZU54XCEKAXVS3VZS","download_json":"https://pith.science/pith/GCZXUIRCVWZU54XCEKAXVS3VZS.json","view_paper":"https://pith.science/paper/GCZXUIRC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1407.2987&json=true","fetch_graph":"https://pith.science/api/pith-number/GCZXUIRCVWZU54XCEKAXVS3VZS/graph.json","fetch_events":"https://pith.science/api/pith-number/GCZXUIRCVWZU54XCEKAXVS3VZS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GCZXUIRCVWZU54XCEKAXVS3VZS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GCZXUIRCVWZU54XCEKAXVS3VZS/action/storage_attestation","attest_author":"https://pith.science/pith/GCZXUIRCVWZU54XCEKAXVS3VZS/action/author_attestation","sign_citation":"https://pith.science/pith/GCZXUIRCVWZU54XCEKAXVS3VZS/action/citation_signature","submit_replication":"https://pith.science/pith/GCZXUIRCVWZU54XCEKAXVS3VZS/action/replication_record"}},"created_at":"2026-05-18T02:47:52.301563+00:00","updated_at":"2026-05-18T02:47:52.301563+00:00"}