{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:WMTFISRIJIUVCTNMW57RHTYLYN","short_pith_number":"pith:WMTFISRI","schema_version":"1.0","canonical_sha256":"b326544a284a29514dacb77f13cf0bc35f9a06a9b21cd8273b942e690b31fa73","source":{"kind":"arxiv","id":"2311.07446","version":1},"attestation_state":"computed","paper":{"title":"Story-to-Motion: Synthesizing Infinite and Controllable Character Animation from Long Text","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Lei Yang, Zhitao Yang, Zhongang Cai, Zhongfei Qing","submitted_at":"2023-11-13T16:22:38Z","abstract_excerpt":"Generating natural human motion from a story has the potential to transform the landscape of animation, gaming, and film industries. A new and challenging task, Story-to-Motion, arises when characters are required to move to various locations and perform specific motions based on a long text description. This task demands a fusion of low-level control (trajectories) and high-level control (motion semantics). Previous works in character control and text-to-motion have addressed related aspects, yet a comprehensive solution remains elusive: character control methods do not handle text descriptio"},"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":"2311.07446","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-13T16:22:38Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"591b7aae879368b055cb7e92638acd5c215f5078e5e8ac44d75a57f332880efb","abstract_canon_sha256":"86d5155ab1abddb416fbc051fef3ff8dd29039d5fd444f2f5a08bcae0dce6c89"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:12:12.602501Z","signature_b64":"uB264PjZe51dgO8iq+NPKwkDssqJDRerZTLmR4i4zOLMBwrzLC+WojsDWkU+pQccVG+Ya9gGBydg4jypoTIlDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b326544a284a29514dacb77f13cf0bc35f9a06a9b21cd8273b942e690b31fa73","last_reissued_at":"2026-07-05T07:12:12.602019Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:12:12.602019Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Story-to-Motion: Synthesizing Infinite and Controllable Character Animation from Long Text","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Lei Yang, Zhitao Yang, Zhongang Cai, Zhongfei Qing","submitted_at":"2023-11-13T16:22:38Z","abstract_excerpt":"Generating natural human motion from a story has the potential to transform the landscape of animation, gaming, and film industries. A new and challenging task, Story-to-Motion, arises when characters are required to move to various locations and perform specific motions based on a long text description. This task demands a fusion of low-level control (trajectories) and high-level control (motion semantics). Previous works in character control and text-to-motion have addressed related aspects, yet a comprehensive solution remains elusive: character control methods do not handle text descriptio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.07446","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/2311.07446/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":"2311.07446","created_at":"2026-07-05T07:12:12.602078+00:00"},{"alias_kind":"arxiv_version","alias_value":"2311.07446v1","created_at":"2026-07-05T07:12:12.602078+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.07446","created_at":"2026-07-05T07:12:12.602078+00:00"},{"alias_kind":"pith_short_12","alias_value":"WMTFISRIJIUV","created_at":"2026-07-05T07:12:12.602078+00:00"},{"alias_kind":"pith_short_16","alias_value":"WMTFISRIJIUVCTNM","created_at":"2026-07-05T07:12:12.602078+00:00"},{"alias_kind":"pith_short_8","alias_value":"WMTFISRI","created_at":"2026-07-05T07:12:12.602078+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2604.25318","citing_title":"Cutscene Agent: An LLM Agent Framework for Automated 3D Cutscene Generation","ref_index":26,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WMTFISRIJIUVCTNMW57RHTYLYN","json":"https://pith.science/pith/WMTFISRIJIUVCTNMW57RHTYLYN.json","graph_json":"https://pith.science/api/pith-number/WMTFISRIJIUVCTNMW57RHTYLYN/graph.json","events_json":"https://pith.science/api/pith-number/WMTFISRIJIUVCTNMW57RHTYLYN/events.json","paper":"https://pith.science/paper/WMTFISRI"},"agent_actions":{"view_html":"https://pith.science/pith/WMTFISRIJIUVCTNMW57RHTYLYN","download_json":"https://pith.science/pith/WMTFISRIJIUVCTNMW57RHTYLYN.json","view_paper":"https://pith.science/paper/WMTFISRI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2311.07446&json=true","fetch_graph":"https://pith.science/api/pith-number/WMTFISRIJIUVCTNMW57RHTYLYN/graph.json","fetch_events":"https://pith.science/api/pith-number/WMTFISRIJIUVCTNMW57RHTYLYN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WMTFISRIJIUVCTNMW57RHTYLYN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WMTFISRIJIUVCTNMW57RHTYLYN/action/storage_attestation","attest_author":"https://pith.science/pith/WMTFISRIJIUVCTNMW57RHTYLYN/action/author_attestation","sign_citation":"https://pith.science/pith/WMTFISRIJIUVCTNMW57RHTYLYN/action/citation_signature","submit_replication":"https://pith.science/pith/WMTFISRIJIUVCTNMW57RHTYLYN/action/replication_record"}},"created_at":"2026-07-05T07:12:12.602078+00:00","updated_at":"2026-07-05T07:12:12.602078+00:00"}