{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:HMALUQT4L5YQ7GACGZRWYSBIZB","short_pith_number":"pith:HMALUQT4","schema_version":"1.0","canonical_sha256":"3b00ba427c5f710f980236636c4828c870e31d969b201dc19e1abe35504412d5","source":{"kind":"arxiv","id":"2305.18009","version":2},"attestation_state":"computed","paper":{"title":"Multi-Modal Face Stylization with a Generative Prior","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chongyang Ma, Haibin Huang, Mengtian Li, Minxuan Lin, Pengfei Wan, Yi Dong","submitted_at":"2023-05-29T11:01:31Z","abstract_excerpt":"In this work, we introduce a new approach for face stylization. Despite existing methods achieving impressive results in this task, there is still room for improvement in generating high-quality artistic faces with diverse styles and accurate facial reconstruction. Our proposed framework, MMFS, supports multi-modal face stylization by leveraging the strengths of StyleGAN and integrates it into an encoder-decoder architecture. Specifically, we use the mid-resolution and high-resolution layers of StyleGAN as the decoder to generate high-quality faces, while aligning its low-resolution layer with"},"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":"2305.18009","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-29T11:01:31Z","cross_cats_sorted":[],"title_canon_sha256":"93cf1112834b3d4ce2b8f1ee0dff270e324a2494dc9c2bbc085b57f176b89226","abstract_canon_sha256":"7700bb9f517ea3c37daa104b4dabbf54c31a88df113998eb4f2425a9bac4bd72"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:53:38.428863Z","signature_b64":"qc8fA447Put1L4jeTL2/6BWry9WD6gjvnAjFoMaednDO+WYQtBNFqm4tBnGnADdNpsAnmi/SHOG/92rriGPrBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3b00ba427c5f710f980236636c4828c870e31d969b201dc19e1abe35504412d5","last_reissued_at":"2026-07-05T06:53:38.428370Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:53:38.428370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multi-Modal Face Stylization with a Generative Prior","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chongyang Ma, Haibin Huang, Mengtian Li, Minxuan Lin, Pengfei Wan, Yi Dong","submitted_at":"2023-05-29T11:01:31Z","abstract_excerpt":"In this work, we introduce a new approach for face stylization. Despite existing methods achieving impressive results in this task, there is still room for improvement in generating high-quality artistic faces with diverse styles and accurate facial reconstruction. Our proposed framework, MMFS, supports multi-modal face stylization by leveraging the strengths of StyleGAN and integrates it into an encoder-decoder architecture. Specifically, we use the mid-resolution and high-resolution layers of StyleGAN as the decoder to generate high-quality faces, while aligning its low-resolution layer with"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.18009","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2305.18009/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":"2305.18009","created_at":"2026-07-05T06:53:38.428428+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.18009v2","created_at":"2026-07-05T06:53:38.428428+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.18009","created_at":"2026-07-05T06:53:38.428428+00:00"},{"alias_kind":"pith_short_12","alias_value":"HMALUQT4L5YQ","created_at":"2026-07-05T06:53:38.428428+00:00"},{"alias_kind":"pith_short_16","alias_value":"HMALUQT4L5YQ7GAC","created_at":"2026-07-05T06:53:38.428428+00:00"},{"alias_kind":"pith_short_8","alias_value":"HMALUQT4","created_at":"2026-07-05T06:53:38.428428+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/HMALUQT4L5YQ7GACGZRWYSBIZB","json":"https://pith.science/pith/HMALUQT4L5YQ7GACGZRWYSBIZB.json","graph_json":"https://pith.science/api/pith-number/HMALUQT4L5YQ7GACGZRWYSBIZB/graph.json","events_json":"https://pith.science/api/pith-number/HMALUQT4L5YQ7GACGZRWYSBIZB/events.json","paper":"https://pith.science/paper/HMALUQT4"},"agent_actions":{"view_html":"https://pith.science/pith/HMALUQT4L5YQ7GACGZRWYSBIZB","download_json":"https://pith.science/pith/HMALUQT4L5YQ7GACGZRWYSBIZB.json","view_paper":"https://pith.science/paper/HMALUQT4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.18009&json=true","fetch_graph":"https://pith.science/api/pith-number/HMALUQT4L5YQ7GACGZRWYSBIZB/graph.json","fetch_events":"https://pith.science/api/pith-number/HMALUQT4L5YQ7GACGZRWYSBIZB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HMALUQT4L5YQ7GACGZRWYSBIZB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HMALUQT4L5YQ7GACGZRWYSBIZB/action/storage_attestation","attest_author":"https://pith.science/pith/HMALUQT4L5YQ7GACGZRWYSBIZB/action/author_attestation","sign_citation":"https://pith.science/pith/HMALUQT4L5YQ7GACGZRWYSBIZB/action/citation_signature","submit_replication":"https://pith.science/pith/HMALUQT4L5YQ7GACGZRWYSBIZB/action/replication_record"}},"created_at":"2026-07-05T06:53:38.428428+00:00","updated_at":"2026-07-05T06:53:38.428428+00:00"}