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.
Overview
We introduce MovieCharacter, a straightforward yet effective tuning-free framework designed for character video synthesis. This framework enables users to initiate synthesis with a selected movie and customize characters by decomposing the synthesis problem into distinct components, including character segmentation and tracking, object removal, character motion imitation, and video composition.
Each of these independent modules is designed to function collaboratively, allowing users to tailor the synthesis process according to their specific needs. Character segmentation and tracking facilitate the identification and customization of desired characters, while objective removal enhances the visual coherence by eliminating unwanted elements. Character motion imitation captures realistic movements, and the video composition module ensures the final output meets high-quality standards, thus creating a seamless and interactive user experience.
Limitations and Future Works
Despite achieving outstanding results, our methods still encounter several limitations. Our framework primarily stem from its reliance on the Character Motion Imitation module for character video synthesis in cinematic scenes. Currently, the framework struggles with representing complex action scenarios involving multiple interactions and occlusions effectively. While the overall pipeline established through this work enables the accumulation of data and the refinement of data preprocessing techniques, future efforts will focus on enhancing the capabilities of the Character Motion Imitation module. By addressing these limitations, we aim to improve the framework's performance in more intricate motion contexts, thereby expanding its applicability and effectiveness in diverse cinematic environments.
BibTeX
@misc{qiu2024moviecharacter,
title={MovieCharacter: A Tuning-Free Framework for Controllable Character Video Synthesis},
author={Di Qiu and Zheng Chen and Rui Wang and Mingyuan Fan and Changqian Yu and Junshi Huan and Xiang Wen},
year={2024},
eprint={2410.20974},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2410.20974},
}