{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:3OJ6Z5GLANPSSTOLVAOBWTPDTB","short_pith_number":"pith:3OJ6Z5GL","schema_version":"1.0","canonical_sha256":"db93ecf4cb035f294dcba81c1b4de39860ddea4c95b65686cb4fb395447332c0","source":{"kind":"arxiv","id":"2308.13888","version":4},"attestation_state":"computed","paper":{"title":"Neural Implicit Morphing of Face Images","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Guilherme Schardong, Hallison Paz, Iurii Medvedev, Luiz Velho, Nuno Gon\\c{c}alves, Tiago Novello, Vin\\'icius da Silva","submitted_at":"2023-08-26T14:12:19Z","abstract_excerpt":"Face morphing is a problem in computer graphics with numerous artistic and forensic applications. It is challenging due to variations in pose, lighting, gender, and ethnicity. This task consists of a warping for feature alignment and a blending for a seamless transition between the warped images. We propose to leverage coord-based neural networks to represent such warpings and blendings of face images. During training, we exploit the smoothness and flexibility of such networks by combining energy functionals employed in classical approaches without discretizations. Additionally, our method is "},"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":"2308.13888","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-26T14:12:19Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b09e22c97a32645a7e0e67406b14e53b9ee2994d6842f0e2a4fe3696c62b706b","abstract_canon_sha256":"8e219430fe93a801a7ccb81ab5ad56fcfeed63f8fc2d31c205dcefe8dcd48d13"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:09:53.198732Z","signature_b64":"T4ocM6VYoZAhN88pq6VR4qzq99hJK4nyOAAbckirWd/qNR9Tlim4pWNyoF57Jd7USvWJJfdfG65bk7f5xI4ZDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db93ecf4cb035f294dcba81c1b4de39860ddea4c95b65686cb4fb395447332c0","last_reissued_at":"2026-07-05T09:09:53.198253Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:09:53.198253Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Neural Implicit Morphing of Face Images","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Guilherme Schardong, Hallison Paz, Iurii Medvedev, Luiz Velho, Nuno Gon\\c{c}alves, Tiago Novello, Vin\\'icius da Silva","submitted_at":"2023-08-26T14:12:19Z","abstract_excerpt":"Face morphing is a problem in computer graphics with numerous artistic and forensic applications. It is challenging due to variations in pose, lighting, gender, and ethnicity. This task consists of a warping for feature alignment and a blending for a seamless transition between the warped images. We propose to leverage coord-based neural networks to represent such warpings and blendings of face images. During training, we exploit the smoothness and flexibility of such networks by combining energy functionals employed in classical approaches without discretizations. Additionally, our method is "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.13888","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2308.13888/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2308.13888","created_at":"2026-07-05T09:09:53.198313+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.13888v4","created_at":"2026-07-05T09:09:53.198313+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.13888","created_at":"2026-07-05T09:09:53.198313+00:00"},{"alias_kind":"pith_short_12","alias_value":"3OJ6Z5GLANPS","created_at":"2026-07-05T09:09:53.198313+00:00"},{"alias_kind":"pith_short_16","alias_value":"3OJ6Z5GLANPSSTOL","created_at":"2026-07-05T09:09:53.198313+00:00"},{"alias_kind":"pith_short_8","alias_value":"3OJ6Z5GL","created_at":"2026-07-05T09:09:53.198313+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2604.17338","citing_title":"Precise Debugging Benchmark: Is Your Model Debugging or Regenerating?","ref_index":1,"is_internal_anchor":false},{"citing_arxiv_id":"2604.17338","citing_title":"Precise Debugging Benchmark: Is Your Model Debugging or Regenerating?","ref_index":1,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3OJ6Z5GLANPSSTOLVAOBWTPDTB","json":"https://pith.science/pith/3OJ6Z5GLANPSSTOLVAOBWTPDTB.json","graph_json":"https://pith.science/api/pith-number/3OJ6Z5GLANPSSTOLVAOBWTPDTB/graph.json","events_json":"https://pith.science/api/pith-number/3OJ6Z5GLANPSSTOLVAOBWTPDTB/events.json","paper":"https://pith.science/paper/3OJ6Z5GL"},"agent_actions":{"view_html":"https://pith.science/pith/3OJ6Z5GLANPSSTOLVAOBWTPDTB","download_json":"https://pith.science/pith/3OJ6Z5GLANPSSTOLVAOBWTPDTB.json","view_paper":"https://pith.science/paper/3OJ6Z5GL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.13888&json=true","fetch_graph":"https://pith.science/api/pith-number/3OJ6Z5GLANPSSTOLVAOBWTPDTB/graph.json","fetch_events":"https://pith.science/api/pith-number/3OJ6Z5GLANPSSTOLVAOBWTPDTB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3OJ6Z5GLANPSSTOLVAOBWTPDTB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3OJ6Z5GLANPSSTOLVAOBWTPDTB/action/storage_attestation","attest_author":"https://pith.science/pith/3OJ6Z5GLANPSSTOLVAOBWTPDTB/action/author_attestation","sign_citation":"https://pith.science/pith/3OJ6Z5GLANPSSTOLVAOBWTPDTB/action/citation_signature","submit_replication":"https://pith.science/pith/3OJ6Z5GLANPSSTOLVAOBWTPDTB/action/replication_record"}},"created_at":"2026-07-05T09:09:53.198313+00:00","updated_at":"2026-07-05T09:09:53.198313+00:00"}