DexYCB: A Benchmark for Capturing Hand Grasping of Objects

• URL: http://arxiv.org/abs/2104.04631v1
• Date: Fri, 9 Apr 2021 22:54:21 GMT
• Title: DexYCB: A Benchmark for Capturing Hand Grasping of Objects
• Authors: 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
• Abstract summary: We introduce DexYCB, a new dataset for capturing hand grasping of objects. We present a benchmark of state-of-the-art approaches on three relevant tasks. We then evaluate a new robotics-relevant task: generating safe robot grasps in human-to-robot object handover.
• Score: 101.48808584983867
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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