{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:FBON5ESMHSWAX3RNYDHZBBB4YE","short_pith_number":"pith:FBON5ESM","schema_version":"1.0","canonical_sha256":"285cde924c3cac0bee2dc0cf90843cc10c24d00c04e31ec317f7cf3051b8a512","source":{"kind":"arxiv","id":"2401.09146","version":1},"attestation_state":"computed","paper":{"title":"Continuous Piecewise-Affine Based Motion Model for Image Animation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fengqi Liu, Hexiang Wang, Lizhuang Ma, Qianyu Zhou, Ran Yi, Xin Tan","submitted_at":"2024-01-17T11:40:05Z","abstract_excerpt":"Image animation aims to bring static images to life according to driving videos and create engaging visual content that can be used for various purposes such as animation, entertainment, and education. Recent unsupervised methods utilize affine and thin-plate spline transformations based on keypoints to transfer the motion in driving frames to the source image. However, limited by the expressive power of the transformations used, these methods always produce poor results when the gap between the motion in the driving frame and the source image is large. To address this issue, we propose to mod"},"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":"2401.09146","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-01-17T11:40:05Z","cross_cats_sorted":[],"title_canon_sha256":"a99efca62d33356d65c90d4cde5fb78713ba66835f92fb38a17b46e07c82972c","abstract_canon_sha256":"4944b2a12835cfff1fd56d6f230ac3a734397503bc778ea161df5d66ea820ca5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:34:40.152169Z","signature_b64":"orW6FZ+lUumUDJnX5tejs7NrZQPrVKao+CVOeFV2AIqYR+mW8/WSmv5i8tYUgU4QOASuk0JWdr9Cy04ueoEmBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"285cde924c3cac0bee2dc0cf90843cc10c24d00c04e31ec317f7cf3051b8a512","last_reissued_at":"2026-07-05T07:34:40.151825Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:34:40.151825Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Continuous Piecewise-Affine Based Motion Model for Image Animation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fengqi Liu, Hexiang Wang, Lizhuang Ma, Qianyu Zhou, Ran Yi, Xin Tan","submitted_at":"2024-01-17T11:40:05Z","abstract_excerpt":"Image animation aims to bring static images to life according to driving videos and create engaging visual content that can be used for various purposes such as animation, entertainment, and education. Recent unsupervised methods utilize affine and thin-plate spline transformations based on keypoints to transfer the motion in driving frames to the source image. However, limited by the expressive power of the transformations used, these methods always produce poor results when the gap between the motion in the driving frame and the source image is large. To address this issue, we propose to mod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.09146","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/2401.09146/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":"2401.09146","created_at":"2026-07-05T07:34:40.151873+00:00"},{"alias_kind":"arxiv_version","alias_value":"2401.09146v1","created_at":"2026-07-05T07:34:40.151873+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.09146","created_at":"2026-07-05T07:34:40.151873+00:00"},{"alias_kind":"pith_short_12","alias_value":"FBON5ESMHSWA","created_at":"2026-07-05T07:34:40.151873+00:00"},{"alias_kind":"pith_short_16","alias_value":"FBON5ESMHSWAX3RN","created_at":"2026-07-05T07:34:40.151873+00:00"},{"alias_kind":"pith_short_8","alias_value":"FBON5ESM","created_at":"2026-07-05T07:34:40.151873+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2502.06029","citing_title":"DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations","ref_index":49,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FBON5ESMHSWAX3RNYDHZBBB4YE","json":"https://pith.science/pith/FBON5ESMHSWAX3RNYDHZBBB4YE.json","graph_json":"https://pith.science/api/pith-number/FBON5ESMHSWAX3RNYDHZBBB4YE/graph.json","events_json":"https://pith.science/api/pith-number/FBON5ESMHSWAX3RNYDHZBBB4YE/events.json","paper":"https://pith.science/paper/FBON5ESM"},"agent_actions":{"view_html":"https://pith.science/pith/FBON5ESMHSWAX3RNYDHZBBB4YE","download_json":"https://pith.science/pith/FBON5ESMHSWAX3RNYDHZBBB4YE.json","view_paper":"https://pith.science/paper/FBON5ESM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2401.09146&json=true","fetch_graph":"https://pith.science/api/pith-number/FBON5ESMHSWAX3RNYDHZBBB4YE/graph.json","fetch_events":"https://pith.science/api/pith-number/FBON5ESMHSWAX3RNYDHZBBB4YE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FBON5ESMHSWAX3RNYDHZBBB4YE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FBON5ESMHSWAX3RNYDHZBBB4YE/action/storage_attestation","attest_author":"https://pith.science/pith/FBON5ESMHSWAX3RNYDHZBBB4YE/action/author_attestation","sign_citation":"https://pith.science/pith/FBON5ESMHSWAX3RNYDHZBBB4YE/action/citation_signature","submit_replication":"https://pith.science/pith/FBON5ESMHSWAX3RNYDHZBBB4YE/action/replication_record"}},"created_at":"2026-07-05T07:34:40.151873+00:00","updated_at":"2026-07-05T07:34:40.151873+00:00"}