Authors: Yiheng Huang, Hui Yang, Chuanchen Luo, Yuxi Wang, Shibiao Xu, Zhaoxiang Zhang, Man Zhang, Junran Peng

Published on: May 09, 2024

Impact Score: 7.2

Arxiv code: Arxiv:2405.05691

Summary

• What is new: StableMoFusion, a tailored approach for human motion generation that addresses and corrects foot skating issues.
• Why this is important: Existing diffusion-based methods for human motion generation have unclear component design effects and are too computationally hefty for real-time use.
• What the research proposes: A comprehensive investigation leading to a specialized model that eliminates foot skating and optimizes computational efficiency.
• Results: StableMoFusion shows promising performance improvements over current state-of-the-art methods in generating human motion.

Technical Details

Technological frameworks used: StableMoFusion

Models used: Diffusion models for motion generation, foot-ground contact identification techniques

Data used: nan

Potential Impact

Virtual reality, video game development, animation studios, robotics

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