DexYCB: A Benchmark for Capturing Hand Grasping of Objects
Yu-Wei Chao, Wei Yang, Xiang Yu, Pavlo Molchanov, Ankur Handa, Jonathan Tremblay, Yashraj Narang, Karl Van Wyk, Umar Iqbal, Stan Birchfield, Jan Kautz, Dieter Fox
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. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>
Topics & Concepts
Benchmark (surveying)Artificial intelligenceComputer sciencePoseObject (grammar)Task (project management)RoboticsRobotComputer visionHandoverObject detectionPattern recognition (psychology)EngineeringComputer networkGeographyGeodesySystems engineeringRobot Manipulation and LearningHand Gesture Recognition SystemsHuman Pose and Action Recognition