Paper Info
Title
DexYCB: A Benchmark for Capturing Hand Grasping of Objects
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.(1)
Year
DOI
Venue
2021
10.1109/CVPR46437.2021.00893
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021
DocType
ISSN
Citations 
Conference
1063-6919
0
PageRank 
References 
Authors
0.34
0
12
Name
Order
Citations
PageRank
Yu-Wei Chao12419.87
Wei Yang200.34
Yu Xiang362923.04
Pavlo O. Molchanov419811.96
Ankur Handa547926.11
Jonathan Tremblay67310.97
Yashraj S. Narang700.34
Karl Van Wyk841.17
Umar Iqbal9136.99
Stan Birchfield101406193.73
Jan Kautz113615198.77
Dieter Fox122427249.17