Make-An-Animation: Large-Scale Text-conditional 3D Human Motion Generation

Understand

Text-guided human motion generation has drawn significant interest because of its impactful applications spanning animation and robotics.

• Recently, application of diffusion models for motion generation has enabled improvements in the quality of generated motions.
• However, existing approaches are limited by their reliance on relatively small-scale motion capture data, leading to poor performance on more diverse, in-the-wild prompts.
• In this paper, we introduce Make-An-Animation, a text-conditioned human motion generation model which learns more diverse poses and prompts from large-scale image-text datasets, enabling significant improvement in performance over prior works.