OmniControl: Control Any Joint at Any Time for Human Motion Generation

Yiming Xie, Varun Jampani, Lei Zhong, Deqing Sun, Huaizu Jiang
10/1/2023

No official code found. Best implementation: neu-vi/OmniControl (428 stars, MIT, last commit 2024-06-14).

Abstract

We present a novel approach named OmniControl for incorporating flexible spatial control signals into a text-conditioned human motion generation model based on the diffusion process. Unlike previous methods that can only control the pelvis trajectory, OmniControl can incorporate flexible spatial control signals over different joints at different times with only one model. Specifically, we propose analytic spatial guidance that ensures the generated motion can tightly conform to the input control signals. At the same time, realism guidance is introduced to refine all the joints to generate more coherent motion. Both the spatial and realism guidance are essential and they are highly complementary for balancing control accuracy and motion realism. By combining them, OmniControl generates motions that are realistic, coherent, and consistent with the spatial constraints. Experiments on HumanML3D and KIT-ML datasets show that OmniControl not only achieves significant improvement over state-of-the-art methods on pelvis control but also shows promising results when incorporating the constraints over other joints.

View on arXivView PDF

Code Implementations(1)

neu-vi/OmniControlCommunity100%
MIT

OmniControl: Control Any Joint at Any Time for Human Motion Generation, ICLR 2024

42829Shell, PythonOct 12, 20232 years agoMIT

Similar Papers

Cite this paper

@article{xie2023omnicontrol,
  title  = {OmniControl: Control Any Joint at Any Time for Human Motion Generation},
  author = {Yiming Xie and Varun Jampani and Lei Zhong and Deqing Sun and Huaizu Jiang},
  year   = {2023},
  eprint = {2310.08580},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/pdf/2310.08580},
  journal = {ICLR 2023 2023}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2310.08580.svg)](https://codeofpaper.com/paper/2310.08580)

Discussion