English

DexYCB: A Benchmark for Capturing Hand Grasping of Objects

Computer Vision and Pattern Recognition 2021-04-13 v1

Abstract

We introduce DexYCB, a new dataset for capturing hand grasping of objects. We first compare DexYCB with a related one through cross-dataset evaluation. We then present a thorough benchmark of state-of-the-art approaches on three relevant tasks: 2D object and keypoint detection, 6D object pose estimation, and 3D hand pose estimation. Finally, we evaluate a new robotics-relevant task: generating safe robot grasps in human-to-robot object handover. Dataset and code are available at https://dex-ycb.github.io.

Keywords

Cite

@article{arxiv.2104.04631,
  title  = {DexYCB: A Benchmark for Capturing Hand Grasping of Objects},
  author = {Yu-Wei Chao and Wei Yang and Yu Xiang and Pavlo Molchanov and Ankur Handa and Jonathan Tremblay and Yashraj S. Narang and Karl Van Wyk and Umar Iqbal and Stan Birchfield and Jan Kautz and Dieter Fox},
  journal= {arXiv preprint arXiv:2104.04631},
  year   = {2021}
}

Comments

Accepted to CVPR 2021

R2 v1 2026-06-24T01:01:36.587Z