{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:CKKCL4RAQIZH2JUE5Z4OMU2F7M","short_pith_number":"pith:CKKCL4RA","schema_version":"1.0","canonical_sha256":"129425f22082327d2684ee78e65345fb0381013a430c1f101cf18edcd508a80f","source":{"kind":"arxiv","id":"1409.0602","version":1},"attestation_state":"computed","paper":{"title":"Transferring Landmark Annotations for Cross-Dataset Face Alignment","license":"http://creativecommons.org/licenses/by/3.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chen Change Loy, Cheng Li, Shizhan Zhu, Xiaoou Tang","submitted_at":"2014-09-02T03:36:55Z","abstract_excerpt":"Dataset bias is a well known problem in object recognition domain. This issue, nonetheless, is rarely explored in face alignment research. In this study, we show that dataset plays an integral part of face alignment performance. Specifically, owing to face alignment dataset bias, training on one database and testing on another or unseen domain would lead to poor performance. Creating an unbiased dataset through combining various existing databases, however, is non-trivial as one has to exhaustively re-label the landmarks for standardisation. In this work, we propose a simple and yet effective "},"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":"1409.0602","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/3.0/","primary_cat":"cs.CV","submitted_at":"2014-09-02T03:36:55Z","cross_cats_sorted":[],"title_canon_sha256":"62869cad0284f28610fc8f7d41767feb177fb43230b179eeaea1eea67bb813c4","abstract_canon_sha256":"6455a63de11581f1d7ff530c90c1618d91423a48f51e9675d0e829b31a04b3bd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:43:46.508065Z","signature_b64":"m/tgV6UjSSINVFSE0g2xRPNbm1dGI8yt080/UTrNwqd5+zSed/W82Kx4AaJzZHtDwDSbojrE+4DtPZxQf1NdCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"129425f22082327d2684ee78e65345fb0381013a430c1f101cf18edcd508a80f","last_reissued_at":"2026-05-18T02:43:46.507677Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:43:46.507677Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Transferring Landmark Annotations for Cross-Dataset Face Alignment","license":"http://creativecommons.org/licenses/by/3.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chen Change Loy, Cheng Li, Shizhan Zhu, Xiaoou Tang","submitted_at":"2014-09-02T03:36:55Z","abstract_excerpt":"Dataset bias is a well known problem in object recognition domain. This issue, nonetheless, is rarely explored in face alignment research. In this study, we show that dataset plays an integral part of face alignment performance. Specifically, owing to face alignment dataset bias, training on one database and testing on another or unseen domain would lead to poor performance. Creating an unbiased dataset through combining various existing databases, however, is non-trivial as one has to exhaustively re-label the landmarks for standardisation. In this work, we propose a simple and yet effective "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1409.0602","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":"1409.0602","created_at":"2026-05-18T02:43:46.507730+00:00"},{"alias_kind":"arxiv_version","alias_value":"1409.0602v1","created_at":"2026-05-18T02:43:46.507730+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1409.0602","created_at":"2026-05-18T02:43:46.507730+00:00"},{"alias_kind":"pith_short_12","alias_value":"CKKCL4RAQIZH","created_at":"2026-05-18T12:28:22.404517+00:00"},{"alias_kind":"pith_short_16","alias_value":"CKKCL4RAQIZH2JUE","created_at":"2026-05-18T12:28:22.404517+00:00"},{"alias_kind":"pith_short_8","alias_value":"CKKCL4RA","created_at":"2026-05-18T12:28:22.404517+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/CKKCL4RAQIZH2JUE5Z4OMU2F7M","json":"https://pith.science/pith/CKKCL4RAQIZH2JUE5Z4OMU2F7M.json","graph_json":"https://pith.science/api/pith-number/CKKCL4RAQIZH2JUE5Z4OMU2F7M/graph.json","events_json":"https://pith.science/api/pith-number/CKKCL4RAQIZH2JUE5Z4OMU2F7M/events.json","paper":"https://pith.science/paper/CKKCL4RA"},"agent_actions":{"view_html":"https://pith.science/pith/CKKCL4RAQIZH2JUE5Z4OMU2F7M","download_json":"https://pith.science/pith/CKKCL4RAQIZH2JUE5Z4OMU2F7M.json","view_paper":"https://pith.science/paper/CKKCL4RA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1409.0602&json=true","fetch_graph":"https://pith.science/api/pith-number/CKKCL4RAQIZH2JUE5Z4OMU2F7M/graph.json","fetch_events":"https://pith.science/api/pith-number/CKKCL4RAQIZH2JUE5Z4OMU2F7M/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CKKCL4RAQIZH2JUE5Z4OMU2F7M/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CKKCL4RAQIZH2JUE5Z4OMU2F7M/action/storage_attestation","attest_author":"https://pith.science/pith/CKKCL4RAQIZH2JUE5Z4OMU2F7M/action/author_attestation","sign_citation":"https://pith.science/pith/CKKCL4RAQIZH2JUE5Z4OMU2F7M/action/citation_signature","submit_replication":"https://pith.science/pith/CKKCL4RAQIZH2JUE5Z4OMU2F7M/action/replication_record"}},"created_at":"2026-05-18T02:43:46.507730+00:00","updated_at":"2026-05-18T02:43:46.507730+00:00"}