{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:SD3FVIVYKFOUWH4W62J5JW5JZR","short_pith_number":"pith:SD3FVIVY","schema_version":"1.0","canonical_sha256":"90f65aa2b8515d4b1f96f693d4dba9cc4b15fec1daf2f0875b2d84630a001a07","source":{"kind":"arxiv","id":"1707.03986","version":1},"attestation_state":"computed","paper":{"title":"Merge or Not? Learning to Group Faces via Imitation Learning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Chen Change Loy, Cheng Li, Kaidi Cao, Yue He","submitted_at":"2017-07-13T06:16:43Z","abstract_excerpt":"Given a large number of unlabeled face images, face grouping aims at clustering the images into individual identities present in the data. This task remains a challenging problem despite the remarkable capability of deep learning approaches in learning face representation. In particular, grouping results can still be egregious given profile faces and a large number of uninteresting faces and noisy detections. Often, a user needs to correct the erroneous grouping manually. In this study, we formulate a novel face grouping framework that learns clustering strategy from ground-truth simulated beh"},"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":"1707.03986","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2017-07-13T06:16:43Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"294470e7a15f5ec419a074cbda2ac8af8ffc8735cce7da7021f02917d8c7adef","abstract_canon_sha256":"4023ef5486540ddc5cff2886a602e04dc81ce5e861d69704fd9d09ead9328f9e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:40:22.918206Z","signature_b64":"GWGjZ94F+i5HKbm0BerJsu81YCt+kcgrIrS+6icH6Hc2dxCMvfK5nEDjuU3uW2DzQN51kKtZRSbipOxwG2N0Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"90f65aa2b8515d4b1f96f693d4dba9cc4b15fec1daf2f0875b2d84630a001a07","last_reissued_at":"2026-05-18T00:40:22.917640Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:40:22.917640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Merge or Not? Learning to Group Faces via Imitation Learning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Chen Change Loy, Cheng Li, Kaidi Cao, Yue He","submitted_at":"2017-07-13T06:16:43Z","abstract_excerpt":"Given a large number of unlabeled face images, face grouping aims at clustering the images into individual identities present in the data. This task remains a challenging problem despite the remarkable capability of deep learning approaches in learning face representation. In particular, grouping results can still be egregious given profile faces and a large number of uninteresting faces and noisy detections. Often, a user needs to correct the erroneous grouping manually. In this study, we formulate a novel face grouping framework that learns clustering strategy from ground-truth simulated beh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.03986","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":"1707.03986","created_at":"2026-05-18T00:40:22.917733+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.03986v1","created_at":"2026-05-18T00:40:22.917733+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.03986","created_at":"2026-05-18T00:40:22.917733+00:00"},{"alias_kind":"pith_short_12","alias_value":"SD3FVIVYKFOU","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_16","alias_value":"SD3FVIVYKFOUWH4W","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_8","alias_value":"SD3FVIVY","created_at":"2026-05-18T12:31:43.269735+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/SD3FVIVYKFOUWH4W62J5JW5JZR","json":"https://pith.science/pith/SD3FVIVYKFOUWH4W62J5JW5JZR.json","graph_json":"https://pith.science/api/pith-number/SD3FVIVYKFOUWH4W62J5JW5JZR/graph.json","events_json":"https://pith.science/api/pith-number/SD3FVIVYKFOUWH4W62J5JW5JZR/events.json","paper":"https://pith.science/paper/SD3FVIVY"},"agent_actions":{"view_html":"https://pith.science/pith/SD3FVIVYKFOUWH4W62J5JW5JZR","download_json":"https://pith.science/pith/SD3FVIVYKFOUWH4W62J5JW5JZR.json","view_paper":"https://pith.science/paper/SD3FVIVY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.03986&json=true","fetch_graph":"https://pith.science/api/pith-number/SD3FVIVYKFOUWH4W62J5JW5JZR/graph.json","fetch_events":"https://pith.science/api/pith-number/SD3FVIVYKFOUWH4W62J5JW5JZR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SD3FVIVYKFOUWH4W62J5JW5JZR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SD3FVIVYKFOUWH4W62J5JW5JZR/action/storage_attestation","attest_author":"https://pith.science/pith/SD3FVIVYKFOUWH4W62J5JW5JZR/action/author_attestation","sign_citation":"https://pith.science/pith/SD3FVIVYKFOUWH4W62J5JW5JZR/action/citation_signature","submit_replication":"https://pith.science/pith/SD3FVIVYKFOUWH4W62J5JW5JZR/action/replication_record"}},"created_at":"2026-05-18T00:40:22.917733+00:00","updated_at":"2026-05-18T00:40:22.917733+00:00"}