Deep-Motion-Editing enables deep learning-based manipulation of 3D character animations. This library offers modules for motion retargeting, transferring motion from one character to another, and style transfer, which allows applying the motion style of one character to another. The core problem addressed is the need for robust and flexible tools for editing complex 3D character animations, leveraging deep learning techniques.
The library features well-defined modules for motion retargeting and style transfer based on publications from SIGGRAPH 2020. It supports both in-sample and unpaired data training scenarios. The project provides clear instructions for data preparation and model training, and offers pre-trained models for quick experimentation. The architecture allows for easy extension with new editing operations and character meshes.
- Motion Retargeting: Allows transferring motion from a source skeleton to a target skeleton using deep learning.
- Motion Style Transfer: Enables transferring motion styles between different 3D characters, using either 3D mocap data or 2D video keypoints.
- Pretrained Models: Provides pre-trained models for quick experimentation and evaluation.
- Ease of Use: Offers well-documented training and usage instructions with example scripts.
- Flexibility: Supports both in-sample and unpaired training for motion retargeting and style transfer.
The project is actively maintained with recent commits and a consistent release history. Documentation is present, although can be expanded, and the community engagement is demonstrated through the number of stars and forks. Regular updates and improvements are provided, suggesting ongoing development and support.
This project benefits researchers and developers working on 3D character animation, computer graphics, and deep learning. It enables advanced animation editing workflows for tasks like motion retargeting, style transfer, and automated animation generation. It is useful for researchers needing a foundation for these techniques and developers seeking to integrate deep learning-based motion editing into their applications.