{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:RC74DF5DEWORP5J626HIKJLLOU","short_pith_number":"pith:RC74DF5D","schema_version":"1.0","canonical_sha256":"88bfc197a3259d17f53ed78e85256b75294a679e4e78e89c8365e1a66cbf4264","source":{"kind":"arxiv","id":"1908.07191","version":1},"attestation_state":"computed","paper":{"title":"Make a Face: Towards Arbitrary High Fidelity Face Manipulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chen Qian, Fumin Shen, Kwan-Yee Lin, Quan Wang, Ran He, Shengju Qian, Wayne Wu, Yangxiaokang Liu","submitted_at":"2019-08-20T06:53:55Z","abstract_excerpt":"Recent studies have shown remarkable success in face manipulation task with the advance of GANs and VAEs paradigms, but the outputs are sometimes limited to low-resolution and lack of diversity.\n  In this work, we propose Additive Focal Variational Auto-encoder (AF-VAE), a novel approach that can arbitrarily manipulate high-resolution face images using a simple yet effective model and only weak supervision of reconstruction and KL divergence losses. First, a novel additive Gaussian Mixture assumption is introduced with an unsupervised clustering mechanism in the structural latent space, which "},"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":"1908.07191","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-20T06:53:55Z","cross_cats_sorted":[],"title_canon_sha256":"acec65d915c6d54983fc5e389656aaea1d8ddee5701be72c971d296203729c8c","abstract_canon_sha256":"60df1b497c419ffef7448aa5ba1fd1f839594e2cc0060c3937099bda1bb51da5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:58:31.775405Z","signature_b64":"HLUzchA+O60OeX5r3n7O/he6Q3e6rnPvFtQkxW0HaCiULSZ1q5/XP4CLHmPF7aDGrlZ/RseMzyk+AyEqWOcACQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"88bfc197a3259d17f53ed78e85256b75294a679e4e78e89c8365e1a66cbf4264","last_reissued_at":"2026-07-04T23:58:31.775049Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:58:31.775049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Make a Face: Towards Arbitrary High Fidelity Face Manipulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chen Qian, Fumin Shen, Kwan-Yee Lin, Quan Wang, Ran He, Shengju Qian, Wayne Wu, Yangxiaokang Liu","submitted_at":"2019-08-20T06:53:55Z","abstract_excerpt":"Recent studies have shown remarkable success in face manipulation task with the advance of GANs and VAEs paradigms, but the outputs are sometimes limited to low-resolution and lack of diversity.\n  In this work, we propose Additive Focal Variational Auto-encoder (AF-VAE), a novel approach that can arbitrarily manipulate high-resolution face images using a simple yet effective model and only weak supervision of reconstruction and KL divergence losses. First, a novel additive Gaussian Mixture assumption is introduced with an unsupervised clustering mechanism in the structural latent space, which "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.07191","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.07191/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":"1908.07191","created_at":"2026-07-04T23:58:31.775104+00:00"},{"alias_kind":"arxiv_version","alias_value":"1908.07191v1","created_at":"2026-07-04T23:58:31.775104+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.07191","created_at":"2026-07-04T23:58:31.775104+00:00"},{"alias_kind":"pith_short_12","alias_value":"RC74DF5DEWOR","created_at":"2026-07-04T23:58:31.775104+00:00"},{"alias_kind":"pith_short_16","alias_value":"RC74DF5DEWORP5J6","created_at":"2026-07-04T23:58:31.775104+00:00"},{"alias_kind":"pith_short_8","alias_value":"RC74DF5D","created_at":"2026-07-04T23:58:31.775104+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/RC74DF5DEWORP5J626HIKJLLOU","json":"https://pith.science/pith/RC74DF5DEWORP5J626HIKJLLOU.json","graph_json":"https://pith.science/api/pith-number/RC74DF5DEWORP5J626HIKJLLOU/graph.json","events_json":"https://pith.science/api/pith-number/RC74DF5DEWORP5J626HIKJLLOU/events.json","paper":"https://pith.science/paper/RC74DF5D"},"agent_actions":{"view_html":"https://pith.science/pith/RC74DF5DEWORP5J626HIKJLLOU","download_json":"https://pith.science/pith/RC74DF5DEWORP5J626HIKJLLOU.json","view_paper":"https://pith.science/paper/RC74DF5D","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1908.07191&json=true","fetch_graph":"https://pith.science/api/pith-number/RC74DF5DEWORP5J626HIKJLLOU/graph.json","fetch_events":"https://pith.science/api/pith-number/RC74DF5DEWORP5J626HIKJLLOU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RC74DF5DEWORP5J626HIKJLLOU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RC74DF5DEWORP5J626HIKJLLOU/action/storage_attestation","attest_author":"https://pith.science/pith/RC74DF5DEWORP5J626HIKJLLOU/action/author_attestation","sign_citation":"https://pith.science/pith/RC74DF5DEWORP5J626HIKJLLOU/action/citation_signature","submit_replication":"https://pith.science/pith/RC74DF5DEWORP5J626HIKJLLOU/action/replication_record"}},"created_at":"2026-07-04T23:58:31.775104+00:00","updated_at":"2026-07-04T23:58:31.775104+00:00"}