{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:YJEP2N5TCMAM3LEEJ4FMNBVMFP","short_pith_number":"pith:YJEP2N5T","canonical_record":{"source":{"id":"2109.00471","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-01T16:23:57Z","cross_cats_sorted":[],"title_canon_sha256":"19145cbea227273be3c5d6476fe4d0e0225c39319dfe5b37eea3fee53645b6dc","abstract_canon_sha256":"003090d6f9d1d675309d7148d9fa6eb98931cc9f9698e04c4794d359803fc309"},"schema_version":"1.0"},"canonical_sha256":"c248fd37b31300cdac844f0ac686ac2bd4212525debbb1ef11027db4fa328112","source":{"kind":"arxiv","id":"2109.00471","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.00471","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"arxiv_version","alias_value":"2109.00471v2","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.00471","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"pith_short_12","alias_value":"YJEP2N5TCMAM","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"pith_short_16","alias_value":"YJEP2N5TCMAM3LEE","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"pith_short_8","alias_value":"YJEP2N5T","created_at":"2026-07-05T03:11:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:YJEP2N5TCMAM3LEEJ4FMNBVMFP","target":"record","payload":{"canonical_record":{"source":{"id":"2109.00471","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-01T16:23:57Z","cross_cats_sorted":[],"title_canon_sha256":"19145cbea227273be3c5d6476fe4d0e0225c39319dfe5b37eea3fee53645b6dc","abstract_canon_sha256":"003090d6f9d1d675309d7148d9fa6eb98931cc9f9698e04c4794d359803fc309"},"schema_version":"1.0"},"canonical_sha256":"c248fd37b31300cdac844f0ac686ac2bd4212525debbb1ef11027db4fa328112","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:11:14.968215Z","signature_b64":"83KsrdrAc1GKPNxFpYRiZ8c30CMVgQSF9xGQo7Dgc016m77v3jcNHW0DmEHYep5z9hBoz85ROHyGQF/czCiOBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c248fd37b31300cdac844f0ac686ac2bd4212525debbb1ef11027db4fa328112","last_reissued_at":"2026-07-05T03:11:14.967826Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:11:14.967826Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2109.00471","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:11:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LlUVFWPSxQMUYkHOi16gNa6Ngtjj6lLPV//32Zu4MiVmvj3kpiT2crQzO/ION017lTQ7KqWlFb+3YSkQqtJYDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T09:21:07.687945Z"},"content_sha256":"b00f97f3ca57c21a2ab899a087550bb64b8bb272ee46b9760c83f586f437a441","schema_version":"1.0","event_id":"sha256:b00f97f3ca57c21a2ab899a087550bb64b8bb272ee46b9760c83f586f437a441"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:YJEP2N5TCMAM3LEEJ4FMNBVMFP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sparse to Dense Motion Transfer for Face Image Animation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guodong Guo, Ruiqi Zhao, Tianyi Wu","submitted_at":"2021-09-01T16:23:57Z","abstract_excerpt":"Face image animation from a single image has achieved remarkable progress. However, it remains challenging when only sparse landmarks are available as the driving signal. Given a source face image and a sequence of sparse face landmarks, our goal is to generate a video of the face imitating the motion of landmarks. We develop an efficient and effective method for motion transfer from sparse landmarks to the face image. We then combine global and local motion estimation in a unified model to faithfully transfer the motion. The model can learn to segment the moving foreground from the background"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.00471","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/2109.00471/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":"2026-07-05T03:11:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uYyqsaPLhF+zbyvonXVZuVC0OCVoJBEz85sneAGbhr+aP9NYe7il0ZTkcX2nSs3JgUC0LlSpOCWHtdy2hBwsDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T09:21:07.688537Z"},"content_sha256":"482e60aad89135092106d24765b62dad10a9453ff6236c754e57c53ef4c01988","schema_version":"1.0","event_id":"sha256:482e60aad89135092106d24765b62dad10a9453ff6236c754e57c53ef4c01988"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YJEP2N5TCMAM3LEEJ4FMNBVMFP/bundle.json","state_url":"https://pith.science/pith/YJEP2N5TCMAM3LEEJ4FMNBVMFP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YJEP2N5TCMAM3LEEJ4FMNBVMFP/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":"2026-08-14T09:21:07Z","links":{"resolver":"https://pith.science/pith/YJEP2N5TCMAM3LEEJ4FMNBVMFP","bundle":"https://pith.science/pith/YJEP2N5TCMAM3LEEJ4FMNBVMFP/bundle.json","state":"https://pith.science/pith/YJEP2N5TCMAM3LEEJ4FMNBVMFP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YJEP2N5TCMAM3LEEJ4FMNBVMFP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:YJEP2N5TCMAM3LEEJ4FMNBVMFP","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":"003090d6f9d1d675309d7148d9fa6eb98931cc9f9698e04c4794d359803fc309","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-01T16:23:57Z","title_canon_sha256":"19145cbea227273be3c5d6476fe4d0e0225c39319dfe5b37eea3fee53645b6dc"},"schema_version":"1.0","source":{"id":"2109.00471","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.00471","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"arxiv_version","alias_value":"2109.00471v2","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.00471","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"pith_short_12","alias_value":"YJEP2N5TCMAM","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"pith_short_16","alias_value":"YJEP2N5TCMAM3LEE","created_at":"2026-07-05T03:11:14Z"},{"alias_kind":"pith_short_8","alias_value":"YJEP2N5T","created_at":"2026-07-05T03:11:14Z"}],"graph_snapshots":[{"event_id":"sha256:482e60aad89135092106d24765b62dad10a9453ff6236c754e57c53ef4c01988","target":"graph","created_at":"2026-07-05T03:11:14Z","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/2109.00471/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Face image animation from a single image has achieved remarkable progress. However, it remains challenging when only sparse landmarks are available as the driving signal. Given a source face image and a sequence of sparse face landmarks, our goal is to generate a video of the face imitating the motion of landmarks. We develop an efficient and effective method for motion transfer from sparse landmarks to the face image. We then combine global and local motion estimation in a unified model to faithfully transfer the motion. The model can learn to segment the moving foreground from the background","authors_text":"Guodong Guo, Ruiqi Zhao, Tianyi Wu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-01T16:23:57Z","title":"Sparse to Dense Motion Transfer for Face Image Animation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.00471","kind":"arxiv","version":2},"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:b00f97f3ca57c21a2ab899a087550bb64b8bb272ee46b9760c83f586f437a441","target":"record","created_at":"2026-07-05T03:11:14Z","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":"003090d6f9d1d675309d7148d9fa6eb98931cc9f9698e04c4794d359803fc309","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-01T16:23:57Z","title_canon_sha256":"19145cbea227273be3c5d6476fe4d0e0225c39319dfe5b37eea3fee53645b6dc"},"schema_version":"1.0","source":{"id":"2109.00471","kind":"arxiv","version":2}},"canonical_sha256":"c248fd37b31300cdac844f0ac686ac2bd4212525debbb1ef11027db4fa328112","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c248fd37b31300cdac844f0ac686ac2bd4212525debbb1ef11027db4fa328112","first_computed_at":"2026-07-05T03:11:14.967826Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:11:14.967826Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"83KsrdrAc1GKPNxFpYRiZ8c30CMVgQSF9xGQo7Dgc016m77v3jcNHW0DmEHYep5z9hBoz85ROHyGQF/czCiOBA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:11:14.968215Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.00471","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b00f97f3ca57c21a2ab899a087550bb64b8bb272ee46b9760c83f586f437a441","sha256:482e60aad89135092106d24765b62dad10a9453ff6236c754e57c53ef4c01988"],"state_sha256":"eccaa3320775693b7d35c6cda109ec9462b489b15395ae5ada15361cfd415afc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WJX6cjN+f25J3ZJj/hVhJWdvjyyYDEP29LpAfArd8fl7SpTFFQAzDNkLrlvJy26d4K+ZE8dRNteZMcEFyeE+Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T09:21:07.694500Z","bundle_sha256":"c806cb6b79d10e0d146a8a3cb4593e7e7af661fb9c9189468a81c4405b61b644"}}