StableMoFusion: Towards Robust and Efficient Diffusion-based Motion Generation Framework

Understand

Thanks to the powerful generative capacity of diffusion models, recent years have witnessed rapid progress in human motion generation.

• Existing diffusion-based methods employ disparate network architectures and training strategies.
• The effect of the design of each component is still unclear.
• In addition, the iterative denoising process consumes considerable computational overhead, which is prohibitive for real-time scenarios such as virtual characters and humanoid robots.