{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:PH3QZGN7FQTKK3YWBWY7P2NK6M","short_pith_number":"pith:PH3QZGN7","canonical_record":{"source":{"id":"1904.11521","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-25T18:10:27Z","cross_cats_sorted":[],"title_canon_sha256":"2abea45f8d319f04212f619fd04b8fc8b7dc9d5493485cac1fb2b2b3f11493f4","abstract_canon_sha256":"de59752f794a7c28e1bd2eb477465dd66168b82ea0fff170114f56ba9b6e22ac"},"schema_version":"1.0"},"canonical_sha256":"79f70c99bf2c26a56f160db1f7e9aaf320315459b076b0f873cb9b7ac784da56","source":{"kind":"arxiv","id":"1904.11521","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.11521","created_at":"2026-05-17T23:47:43Z"},{"alias_kind":"arxiv_version","alias_value":"1904.11521v1","created_at":"2026-05-17T23:47:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.11521","created_at":"2026-05-17T23:47:43Z"},{"alias_kind":"pith_short_12","alias_value":"PH3QZGN7FQTK","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PH3QZGN7FQTKK3YW","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PH3QZGN7","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:PH3QZGN7FQTKK3YWBWY7P2NK6M","target":"record","payload":{"canonical_record":{"source":{"id":"1904.11521","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-25T18:10:27Z","cross_cats_sorted":[],"title_canon_sha256":"2abea45f8d319f04212f619fd04b8fc8b7dc9d5493485cac1fb2b2b3f11493f4","abstract_canon_sha256":"de59752f794a7c28e1bd2eb477465dd66168b82ea0fff170114f56ba9b6e22ac"},"schema_version":"1.0"},"canonical_sha256":"79f70c99bf2c26a56f160db1f7e9aaf320315459b076b0f873cb9b7ac784da56","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:43.496884Z","signature_b64":"+8q54o+2xsodkGF3W6qn4ym8H146a1G1NL7/QImuDtF/L+tYAu/VQVin1Xmgahf4BrKp5SkCwEf83RTApU+bCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"79f70c99bf2c26a56f160db1f7e9aaf320315459b076b0f873cb9b7ac784da56","last_reissued_at":"2026-05-17T23:47:43.496382Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:43.496382Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.11521","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qXV6gGCWSfZuB7Dxec4Lo9z9QhWInBxvWrHBkPkkhOycfBQLffQWwRIyubLoqzEZHeFceHiLUyT78irhGA3oAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T22:22:57.191191Z"},"content_sha256":"9f53bc092af76c0a356da25804f513cc1b1480c64661b737185a99a4c3f84010","schema_version":"1.0","event_id":"sha256:9f53bc092af76c0a356da25804f513cc1b1480c64661b737185a99a4c3f84010"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:PH3QZGN7FQTKK3YWBWY7P2NK6M","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Face Video Generation from a Single Image and Landmarks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kritaphat Songsri-in, Stefanos Zafeiriou","submitted_at":"2019-04-25T18:10:27Z","abstract_excerpt":"In this paper we are concerned with the challenging problem of producing a full image sequence of a deformable face given only an image and generic facial motions encoded by a set of sparse landmarks. To this end we build upon recent breakthroughs in image-to-image translation such as pix2pix, CycleGAN and StarGAN which learn Deep Convolutional Neural Networks (DCNNs) that learn to map aligned pairs or images between different domains (i.e., having different labels) and propose a new architecture which is not driven any more by labels but by spatial maps, facial landmarks. In particular, we pr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.11521","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X5Qe9ZlEKutnio2TbzVsDktQFEFk4eNC7qHePUuOEuCY2959y42nJofZ9bo8nHmbUnxwRNDjbz2P+6VH6SOzCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T22:22:57.191922Z"},"content_sha256":"64a3b78c44ed8565ae25b18e4229a9c37f91412d75856d6dcd316c2a2c0a8470","schema_version":"1.0","event_id":"sha256:64a3b78c44ed8565ae25b18e4229a9c37f91412d75856d6dcd316c2a2c0a8470"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PH3QZGN7FQTKK3YWBWY7P2NK6M/bundle.json","state_url":"https://pith.science/pith/PH3QZGN7FQTKK3YWBWY7P2NK6M/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PH3QZGN7FQTKK3YWBWY7P2NK6M/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":"2026-06-11T22:22:57Z","links":{"resolver":"https://pith.science/pith/PH3QZGN7FQTKK3YWBWY7P2NK6M","bundle":"https://pith.science/pith/PH3QZGN7FQTKK3YWBWY7P2NK6M/bundle.json","state":"https://pith.science/pith/PH3QZGN7FQTKK3YWBWY7P2NK6M/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PH3QZGN7FQTKK3YWBWY7P2NK6M/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:PH3QZGN7FQTKK3YWBWY7P2NK6M","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":"de59752f794a7c28e1bd2eb477465dd66168b82ea0fff170114f56ba9b6e22ac","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-25T18:10:27Z","title_canon_sha256":"2abea45f8d319f04212f619fd04b8fc8b7dc9d5493485cac1fb2b2b3f11493f4"},"schema_version":"1.0","source":{"id":"1904.11521","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.11521","created_at":"2026-05-17T23:47:43Z"},{"alias_kind":"arxiv_version","alias_value":"1904.11521v1","created_at":"2026-05-17T23:47:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.11521","created_at":"2026-05-17T23:47:43Z"},{"alias_kind":"pith_short_12","alias_value":"PH3QZGN7FQTK","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PH3QZGN7FQTKK3YW","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PH3QZGN7","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:64a3b78c44ed8565ae25b18e4229a9c37f91412d75856d6dcd316c2a2c0a8470","target":"graph","created_at":"2026-05-17T23:47:43Z","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"},"paper":{"abstract_excerpt":"In this paper we are concerned with the challenging problem of producing a full image sequence of a deformable face given only an image and generic facial motions encoded by a set of sparse landmarks. To this end we build upon recent breakthroughs in image-to-image translation such as pix2pix, CycleGAN and StarGAN which learn Deep Convolutional Neural Networks (DCNNs) that learn to map aligned pairs or images between different domains (i.e., having different labels) and propose a new architecture which is not driven any more by labels but by spatial maps, facial landmarks. In particular, we pr","authors_text":"Kritaphat Songsri-in, Stefanos Zafeiriou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-25T18:10:27Z","title":"Face Video Generation from a Single Image and Landmarks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.11521","kind":"arxiv","version":1},"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":"sha256:9f53bc092af76c0a356da25804f513cc1b1480c64661b737185a99a4c3f84010","target":"record","created_at":"2026-05-17T23:47:43Z","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":"de59752f794a7c28e1bd2eb477465dd66168b82ea0fff170114f56ba9b6e22ac","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-25T18:10:27Z","title_canon_sha256":"2abea45f8d319f04212f619fd04b8fc8b7dc9d5493485cac1fb2b2b3f11493f4"},"schema_version":"1.0","source":{"id":"1904.11521","kind":"arxiv","version":1}},"canonical_sha256":"79f70c99bf2c26a56f160db1f7e9aaf320315459b076b0f873cb9b7ac784da56","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"79f70c99bf2c26a56f160db1f7e9aaf320315459b076b0f873cb9b7ac784da56","first_computed_at":"2026-05-17T23:47:43.496382Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:47:43.496382Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+8q54o+2xsodkGF3W6qn4ym8H146a1G1NL7/QImuDtF/L+tYAu/VQVin1Xmgahf4BrKp5SkCwEf83RTApU+bCA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:47:43.496884Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.11521","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9f53bc092af76c0a356da25804f513cc1b1480c64661b737185a99a4c3f84010","sha256:64a3b78c44ed8565ae25b18e4229a9c37f91412d75856d6dcd316c2a2c0a8470"],"state_sha256":"ea2e9420242cf9accac1b66be5e194807e0f9b3a88358cd65d1204f34a4a017d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Usu/R+5/ln2/Uq2Ak8QcOWTrnB0omkiJeFk2qXGl5njMUz5G1gvPtn6zuLwoB4BaEr5tAdCURATZWKevBD4LAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T22:22:57.196007Z","bundle_sha256":"96c9662714bd9af5c3c8913b30c05a36cf1559ea05ce34d6d122eb047ac6ca4d"}}