{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:MTR6Z2TGKFOIM4NVLJZQRFSKI5","short_pith_number":"pith:MTR6Z2TG","canonical_record":{"source":{"id":"1902.03619","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-10T15:15:44Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b42b2bddcf52dd1271419c6e5c437c4ba929dcca6ec97f5e5d967fdd7876d42c","abstract_canon_sha256":"89544d5f81d0050ddd65cd0f074272e38b0d88e7b1bdb31779614bce4ac81bb7"},"schema_version":"1.0"},"canonical_sha256":"64e3ecea66515c8671b55a7308964a477801171a6f73d8e772a889db9e2eb884","source":{"kind":"arxiv","id":"1902.03619","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.03619","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"arxiv_version","alias_value":"1902.03619v3","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.03619","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"pith_short_12","alias_value":"MTR6Z2TGKFOI","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"pith_short_16","alias_value":"MTR6Z2TGKFOIM4NV","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"pith_short_8","alias_value":"MTR6Z2TG","created_at":"2026-07-05T00:02:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:MTR6Z2TGKFOIM4NVLJZQRFSKI5","target":"record","payload":{"canonical_record":{"source":{"id":"1902.03619","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-10T15:15:44Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b42b2bddcf52dd1271419c6e5c437c4ba929dcca6ec97f5e5d967fdd7876d42c","abstract_canon_sha256":"89544d5f81d0050ddd65cd0f074272e38b0d88e7b1bdb31779614bce4ac81bb7"},"schema_version":"1.0"},"canonical_sha256":"64e3ecea66515c8671b55a7308964a477801171a6f73d8e772a889db9e2eb884","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:02:56.904408Z","signature_b64":"P3lIvKMuMyTrF83+zMamq42PFg0WuCI4OJfvy2FBl8bvCujVVFwuMEPTCOrde5bAuzWUdn8pQiIAmvtwxgvKAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"64e3ecea66515c8671b55a7308964a477801171a6f73d8e772a889db9e2eb884","last_reissued_at":"2026-07-05T00:02:56.903990Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:02:56.903990Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.03619","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:02:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+BjI3Xqaf7tZ6drokYV3WPivgZCU4cdPk4UwJ3AJt+Co68DLwYH+AwGPTt1haiSGYfGEvB9j6jLxqPJ5PZa7BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:15:02.201092Z"},"content_sha256":"9405409e5f5ba29f6db514b3d01d285a851da2c6536f82dcdbae22e2e0d66504","schema_version":"1.0","event_id":"sha256:9405409e5f5ba29f6db514b3d01d285a851da2c6536f82dcdbae22e2e0d66504"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:MTR6Z2TGKFOIM4NVLJZQRFSKI5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Decoupled 3D Facial Shape Model by Adversarial Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Adnane Boukhayma, Edmond Boyer, Stefanie Wuhrer, Victoria Fernandez Abrevaya","submitted_at":"2019-02-10T15:15:44Z","abstract_excerpt":"Data-driven generative 3D face models are used to compactly encode facial shape data into meaningful parametric representations. A desirable property of these models is their ability to effectively decouple natural sources of variation, in particular identity and expression. While factorized representations have been proposed for that purpose, they are still limited in the variability they can capture and may present modeling artifacts when applied to tasks such as expression transfer. In this work, we explore a new direction with Generative Adversarial Networks and show that they contribute t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.03619","kind":"arxiv","version":3},"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/1902.03619/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:02:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tyKRH2l1N73s4ZILxuNO5tS6+K4DPBJ+ZxPPW2NnckSu/g3VL6hxsbeLtS+h1YpsE24zhS1DtiSVn6YPVay4AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:15:02.201485Z"},"content_sha256":"ffeacece6bf6905b1f4d16ff53a97b82e4e48ef073753a726873f363e4f899af","schema_version":"1.0","event_id":"sha256:ffeacece6bf6905b1f4d16ff53a97b82e4e48ef073753a726873f363e4f899af"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MTR6Z2TGKFOIM4NVLJZQRFSKI5/bundle.json","state_url":"https://pith.science/pith/MTR6Z2TGKFOIM4NVLJZQRFSKI5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MTR6Z2TGKFOIM4NVLJZQRFSKI5/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T18:15:02Z","links":{"resolver":"https://pith.science/pith/MTR6Z2TGKFOIM4NVLJZQRFSKI5","bundle":"https://pith.science/pith/MTR6Z2TGKFOIM4NVLJZQRFSKI5/bundle.json","state":"https://pith.science/pith/MTR6Z2TGKFOIM4NVLJZQRFSKI5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MTR6Z2TGKFOIM4NVLJZQRFSKI5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:MTR6Z2TGKFOIM4NVLJZQRFSKI5","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"89544d5f81d0050ddd65cd0f074272e38b0d88e7b1bdb31779614bce4ac81bb7","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-10T15:15:44Z","title_canon_sha256":"b42b2bddcf52dd1271419c6e5c437c4ba929dcca6ec97f5e5d967fdd7876d42c"},"schema_version":"1.0","source":{"id":"1902.03619","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.03619","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"arxiv_version","alias_value":"1902.03619v3","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.03619","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"pith_short_12","alias_value":"MTR6Z2TGKFOI","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"pith_short_16","alias_value":"MTR6Z2TGKFOIM4NV","created_at":"2026-07-05T00:02:56Z"},{"alias_kind":"pith_short_8","alias_value":"MTR6Z2TG","created_at":"2026-07-05T00:02:56Z"}],"graph_snapshots":[{"event_id":"sha256:ffeacece6bf6905b1f4d16ff53a97b82e4e48ef073753a726873f363e4f899af","target":"graph","created_at":"2026-07-05T00:02:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1902.03619/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data-driven generative 3D face models are used to compactly encode facial shape data into meaningful parametric representations. A desirable property of these models is their ability to effectively decouple natural sources of variation, in particular identity and expression. While factorized representations have been proposed for that purpose, they are still limited in the variability they can capture and may present modeling artifacts when applied to tasks such as expression transfer. In this work, we explore a new direction with Generative Adversarial Networks and show that they contribute t","authors_text":"Adnane Boukhayma, Edmond Boyer, Stefanie Wuhrer, Victoria Fernandez Abrevaya","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-10T15:15:44Z","title":"A Decoupled 3D Facial Shape Model by Adversarial Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.03619","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:9405409e5f5ba29f6db514b3d01d285a851da2c6536f82dcdbae22e2e0d66504","target":"record","created_at":"2026-07-05T00:02:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"89544d5f81d0050ddd65cd0f074272e38b0d88e7b1bdb31779614bce4ac81bb7","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-10T15:15:44Z","title_canon_sha256":"b42b2bddcf52dd1271419c6e5c437c4ba929dcca6ec97f5e5d967fdd7876d42c"},"schema_version":"1.0","source":{"id":"1902.03619","kind":"arxiv","version":3}},"canonical_sha256":"64e3ecea66515c8671b55a7308964a477801171a6f73d8e772a889db9e2eb884","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"64e3ecea66515c8671b55a7308964a477801171a6f73d8e772a889db9e2eb884","first_computed_at":"2026-07-05T00:02:56.903990Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:02:56.903990Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P3lIvKMuMyTrF83+zMamq42PFg0WuCI4OJfvy2FBl8bvCujVVFwuMEPTCOrde5bAuzWUdn8pQiIAmvtwxgvKAA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:02:56.904408Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.03619","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9405409e5f5ba29f6db514b3d01d285a851da2c6536f82dcdbae22e2e0d66504","sha256:ffeacece6bf6905b1f4d16ff53a97b82e4e48ef073753a726873f363e4f899af"],"state_sha256":"f5a41099fadcccbffdb9b38b1eb81a699aae7d0bbc07907ebcef9f7c1ed21357"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OAcgzs19SCJk2kuEnfKxnOWRYLrYYGJnp/BPg8pn3MjkUceX20B+nyKsF570oFir7Mfkb674mGNAvV3FOzkkCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:15:02.203465Z","bundle_sha256":"10e62ca1ab6dbfd930853a392f167328c0b2d680e6ede78a98a5da0c4ab5c0fb"}}