English

SimpleDepthPose: Fast and Reliable Human Pose Estimation with RGBD-Images

Computer Vision and Pattern Recognition 2025-03-10 v2

Abstract

In the rapidly advancing domain of computer vision, accurately estimating the poses of multiple individuals from various viewpoints remains a significant challenge, especially when reliability is a key requirement. This paper introduces a novel algorithm that excels in multi-view, multi-person pose estimation by incorporating depth information. An extensive evaluation demonstrates that the proposed algorithm not only generalizes well to unseen datasets, and shows a fast runtime performance, but also is adaptable to different keypoints. To support further research, all of the work is publicly accessible.

Keywords

Cite

@article{arxiv.2501.18478,
  title  = {SimpleDepthPose: Fast and Reliable Human Pose Estimation with RGBD-Images},
  author = {Daniel Bermuth and Alexander Poeppel and Wolfgang Reif},
  journal= {arXiv preprint arXiv:2501.18478},
  year   = {2025}
}
R2 v1 2026-06-28T21:25:55.583Z