MovieCharacter: A Tuning-Free Framework for Controllable Character Video Synthesis
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Abstract (arXiv)
Recent advancements in character video synthesis still depend on extensive fine-tuning or complex 3D modeling processes, which can restrict accessibility and hinder real-time applicability. To address these challenges, we propose a simple yet effective tuning-free framework for character video synthesis, named MovieCharacter, designed to streamline the synthesis process while ensuring high-quality outcomes. Our framework decomposes the synthesis task into distinct, manageable modules: character segmentation and tracking, video object removal, character motion imitation, and video composition. This modular design not only facilitates flexible customization but also ensures that each component operates collaboratively to effectively meet user needs. By leveraging existing open-source models and integrating well-established techniques, MovieCharacter achieves impressive synthesis results without necessitating substantial resources or proprietary datasets. Experimental results demonstrate that our framework enhances the efficiency, accessibility, and adaptability of character video synthesis, paving the way for broader creative and interactive applications.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 34 of its 37 references that are in the map. First posted on arXiv 28 Oct 2024.
Builds on
34 of 37 references.
References · 34
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22 more
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Built on by
Citing papers per year: 2025: 10; 2026: 2.
12 papers.
- 2025SkyReels-A2: Compose Anything in Video Diffusion Transformerscited by 72
- 2025Animate Anyone 2: High-Fidelity Character Image Animation with Environment Affordancecited by 60
- 2025SkyReels-A1: Expressive Portrait Animation in Video Diffusion Transformerscited by 33
- 2025Generative AI for Film Creation: A Survey of Recent Advancescited by 17
- 2025Ingredients: Blending Custom Photos with Video Diffusion Transformerscited by 13
- 2025SkyReels-Audio: Omni Audio-Conditioned Talking Portraits in Video Diffusion Transformerscited by 13
- 2025AniCrafter: Customizing Realistic Human-Centric Animation via Avatar-Background Conditioning in Video Diffusion Modelscited by 10
- 2025AnyCharV: Bootstrap Controllable Character Video Generation with Fine-to-Coarse Guidancecited by 2
- 2026SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generationcited by 2
- 2025UniTransfer: Video Concept Transfer via Progressive Spatial and Timestep Decompositioncited by 1
- 2025SwapAnyone: Consistent and Realistic Video Synthesis for Swapping Any Person into Any Videocited by 0
- 2026Customizing Video Portraits via Identity-ActionDecouplingcited by 0
- 2026Customizing Video Portraits via Identity-ActionDecoupling21 Jun 2026
- 2026SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generation11 May 2026
- 2025UniTransfer: Video Concept Transfer via Progressive Spatial and Timestep Decomposition25 Sep 2025
- 2025SkyReels-Audio: Omni Audio-Conditioned Talking Portraits in Video Diffusion Transformers1 Jun 2025
- 2025AniCrafter: Customizing Realistic Human-Centric Animation via Avatar-Background Conditioning in Video Diffusion Models26 May 2025
- 2025Generative AI for Film Creation: A Survey of Recent Advances11 Apr 2025
- 2025SkyReels-A2: Compose Anything in Video Diffusion Transformers3 Apr 2025
- 2025SwapAnyone: Consistent and Realistic Video Synthesis for Swapping Any Person into Any Video12 Mar 2025
- 2025SkyReels-A1: Expressive Portrait Animation in Video Diffusion Transformers15 Feb 2025
- 2025AnyCharV: Bootstrap Controllable Character Video Generation with Fine-to-Coarse Guidance12 Feb 2025
- 2025Animate Anyone 2: High-Fidelity Character Image Animation with Environment Affordance10 Feb 2025
- 2025Ingredients: Blending Custom Photos with Video Diffusion Transformers3 Jan 2025