{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:LBHPFWB2K7D6UODMQMXKXSSRYA","short_pith_number":"pith:LBHPFWB2","schema_version":"1.0","canonical_sha256":"584ef2d83a57c7ea386c832eabca51c03f63fa6c61262d9fe78920a53b90d12b","source":{"kind":"arxiv","id":"2504.08296","version":1},"attestation_state":"computed","paper":{"title":"Generative AI for Film Creation: A Survey of Recent Advances","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anyi Rao, Borou Yu, Ilia Kozlov, Isabela Campillo Valencia, Jiajian Min, Juncheng Nemo Shi, Khushi Hora, Lijian Yang, Mark Chan, Mingzhen Huang, Na Chen, Nix Liu Xin, Patricia Morales Tredinick, Peiwen Huang, Praagya Bahuguna, Ruihan Zhang, Runhe Bian, Shanshan Jiang, Sijia Jiang, Xianghao Kong, Xuanxuan Liu, Yetong Xin, Yongqi Liang, Yunlei Liu, Zheng Wei","submitted_at":"2025-04-11T06:54:29Z","abstract_excerpt":"Generative AI (GenAI) is transforming filmmaking, equipping artists with tools like text-to-image and image-to-video diffusion, neural radiance fields, avatar generation, and 3D synthesis. This paper examines the adoption of these technologies in filmmaking, analyzing workflows from recent AI-driven films to understand how GenAI contributes to character creation, aesthetic styling, and narration. We explore key strategies for maintaining character consistency, achieving stylistic coherence, and ensuring motion continuity. Additionally, we highlight emerging trends such as the growing use of 3D"},"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":"2504.08296","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-11T06:54:29Z","cross_cats_sorted":[],"title_canon_sha256":"021c6c7cff7a67e5b9a1a48a6ff921ed982e34a7b25c4f74af87aadd50a5e797","abstract_canon_sha256":"aed8473340b11b51c9c1358a16cc4772747e75f76767bb13c812490cf1f278c7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:47:46.716341Z","signature_b64":"qw81dbafJSMBrYOGA8CHz8jUzwrKchBgueWimslF2AWKp0nYNSkapLLtQeVgaSxpjSZDQKQGZtlUVfk1osXhBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"584ef2d83a57c7ea386c832eabca51c03f63fa6c61262d9fe78920a53b90d12b","last_reissued_at":"2026-07-05T10:47:46.715835Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:47:46.715835Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Generative AI for Film Creation: A Survey of Recent Advances","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anyi Rao, Borou Yu, Ilia Kozlov, Isabela Campillo Valencia, Jiajian Min, Juncheng Nemo Shi, Khushi Hora, Lijian Yang, Mark Chan, Mingzhen Huang, Na Chen, Nix Liu Xin, Patricia Morales Tredinick, Peiwen Huang, Praagya Bahuguna, Ruihan Zhang, Runhe Bian, Shanshan Jiang, Sijia Jiang, Xianghao Kong, Xuanxuan Liu, Yetong Xin, Yongqi Liang, Yunlei Liu, Zheng Wei","submitted_at":"2025-04-11T06:54:29Z","abstract_excerpt":"Generative AI (GenAI) is transforming filmmaking, equipping artists with tools like text-to-image and image-to-video diffusion, neural radiance fields, avatar generation, and 3D synthesis. This paper examines the adoption of these technologies in filmmaking, analyzing workflows from recent AI-driven films to understand how GenAI contributes to character creation, aesthetic styling, and narration. We explore key strategies for maintaining character consistency, achieving stylistic coherence, and ensuring motion continuity. Additionally, we highlight emerging trends such as the growing use of 3D"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.08296","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/2504.08296/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":"2504.08296","created_at":"2026-07-05T10:47:46.715898+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.08296v1","created_at":"2026-07-05T10:47:46.715898+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.08296","created_at":"2026-07-05T10:47:46.715898+00:00"},{"alias_kind":"pith_short_12","alias_value":"LBHPFWB2K7D6","created_at":"2026-07-05T10:47:46.715898+00:00"},{"alias_kind":"pith_short_16","alias_value":"LBHPFWB2K7D6UODM","created_at":"2026-07-05T10:47:46.715898+00:00"},{"alias_kind":"pith_short_8","alias_value":"LBHPFWB2","created_at":"2026-07-05T10:47:46.715898+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2508.10771","citing_title":"AEGIS: Authenticity Evaluation Benchmark for AI-Generated Video Sequences","ref_index":46,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LBHPFWB2K7D6UODMQMXKXSSRYA","json":"https://pith.science/pith/LBHPFWB2K7D6UODMQMXKXSSRYA.json","graph_json":"https://pith.science/api/pith-number/LBHPFWB2K7D6UODMQMXKXSSRYA/graph.json","events_json":"https://pith.science/api/pith-number/LBHPFWB2K7D6UODMQMXKXSSRYA/events.json","paper":"https://pith.science/paper/LBHPFWB2"},"agent_actions":{"view_html":"https://pith.science/pith/LBHPFWB2K7D6UODMQMXKXSSRYA","download_json":"https://pith.science/pith/LBHPFWB2K7D6UODMQMXKXSSRYA.json","view_paper":"https://pith.science/paper/LBHPFWB2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.08296&json=true","fetch_graph":"https://pith.science/api/pith-number/LBHPFWB2K7D6UODMQMXKXSSRYA/graph.json","fetch_events":"https://pith.science/api/pith-number/LBHPFWB2K7D6UODMQMXKXSSRYA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LBHPFWB2K7D6UODMQMXKXSSRYA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LBHPFWB2K7D6UODMQMXKXSSRYA/action/storage_attestation","attest_author":"https://pith.science/pith/LBHPFWB2K7D6UODMQMXKXSSRYA/action/author_attestation","sign_citation":"https://pith.science/pith/LBHPFWB2K7D6UODMQMXKXSSRYA/action/citation_signature","submit_replication":"https://pith.science/pith/LBHPFWB2K7D6UODMQMXKXSSRYA/action/replication_record"}},"created_at":"2026-07-05T10:47:46.715898+00:00","updated_at":"2026-07-05T10:47:46.715898+00:00"}