MovieCharacter: A Tuning-Free Framework for Controllable Character Video Synthesis

2024-10-28

arXiv.org

AI Summary

Existing character video synthesis methods rely on fine-tuning or complex 3D modeling, resulting in high technical barriers and poor real-time performance—hindering adoption by non-expert users. This paper proposes a fine-tuning-free, modular, and controllable character video synthesis framework that decouples the pipeline into four plug-and-play components: character segmentation and tracking, video object removal, optical-flow-driven motion transfer, and multi-stage video composition. By integrating open-source segmentation/tracking models with state-of-the-art video editing techniques, the framework achieves visual quality comparable to fine-tuned approaches under resource-constrained settings. It significantly improves inference speed (3.2× faster), user controllability, and cross-scenario generalization. To our knowledge, this is the first end-to-end controllable character video synthesis method achieving high fidelity without requiring any fine-tuning or 3D priors—thereby lowering accessibility while preserving quality and control.

Technology Category

• Computer Vision: Computational Photography, Image & Video Synthesis
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Natural Language Processing: Code Generation / Program Synthesis from Natural Language

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

Abstract

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.

Problem

• Real-time Application
• 3D Modeling
• User-friendly Design

Innovation

• SimpleVideoSynthesis
• RealTimeApplication
• UserFriendlyDesign