Generative AI for Film Creation: A Survey of Recent Advances
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arXiv
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866915236847550464 |
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| author | Zhang, Ruihan Yu, Borou Min, Jiajian Xin, Yetong Wei, Zheng Shi, Juncheng Nemo Huang, Mingzhen Kong, Xianghao Xin, Nix Liu Jiang, Shanshan Bahuguna, Praagya Chan, Mark Hora, Khushi Yang, Lijian Liang, Yongqi Bian, Runhe Liu, Yunlei Valencia, Isabela Campillo Tredinick, Patricia Morales Kozlov, Ilia Jiang, Sijia Huang, Peiwen Chen, Na Liu, Xuanxuan Rao, Anyi |
| author_facet | Zhang, Ruihan Yu, Borou Min, Jiajian Xin, Yetong Wei, Zheng Shi, Juncheng Nemo Huang, Mingzhen Kong, Xianghao Xin, Nix Liu Jiang, Shanshan Bahuguna, Praagya Chan, Mark Hora, Khushi Yang, Lijian Liang, Yongqi Bian, Runhe Liu, Yunlei Valencia, Isabela Campillo Tredinick, Patricia Morales Kozlov, Ilia Jiang, Sijia Huang, Peiwen Chen, Na Liu, Xuanxuan Rao, Anyi |
| contents | 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 generation and the integration of real footage with AI-generated elements.
Beyond technical advancements, we examine how GenAI is enabling new artistic expressions, from generating hard-to-shoot footage to dreamlike diffusion-based morphing effects, abstract visuals, and unworldly objects. We also gather artists' feedback on challenges and desired improvements, including consistency, controllability, fine-grained editing, and motion refinement. Our study provides insights into the evolving intersection of AI and filmmaking, offering a roadmap for researchers and artists navigating this rapidly expanding field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_08296 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Generative AI for Film Creation: A Survey of Recent Advances Zhang, Ruihan Yu, Borou Min, Jiajian Xin, Yetong Wei, Zheng Shi, Juncheng Nemo Huang, Mingzhen Kong, Xianghao Xin, Nix Liu Jiang, Shanshan Bahuguna, Praagya Chan, Mark Hora, Khushi Yang, Lijian Liang, Yongqi Bian, Runhe Liu, Yunlei Valencia, Isabela Campillo Tredinick, Patricia Morales Kozlov, Ilia Jiang, Sijia Huang, Peiwen Chen, Na Liu, Xuanxuan Rao, Anyi Computer Vision and Pattern Recognition 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 generation and the integration of real footage with AI-generated elements. Beyond technical advancements, we examine how GenAI is enabling new artistic expressions, from generating hard-to-shoot footage to dreamlike diffusion-based morphing effects, abstract visuals, and unworldly objects. We also gather artists' feedback on challenges and desired improvements, including consistency, controllability, fine-grained editing, and motion refinement. Our study provides insights into the evolving intersection of AI and filmmaking, offering a roadmap for researchers and artists navigating this rapidly expanding field. |
| title | Generative AI for Film Creation: A Survey of Recent Advances |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2504.08296 |