2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.RO2024★ 1 cited
DexGraspNet 2.0: Learning Generative Dexterous Grasping in Large-scale Synthetic Cluttered Scenes
Jialiang Zhang, Haoran Liu, Danshi Li +5
Grasping in cluttered scenes remains highly challenging for dexterous hands due to the scarcity of data. To address this problem, we present a large-scale synthetic benchmark, enco…
cs.RO2023★ 2 cited
UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy
Yinzhen Xu, Weikang Wan, Jialiang Zhang +10
In this work, we tackle the problem of learning universal robotic dexterous grasping from a point cloud observation under a table-top setting. The goal is to grasp and lift up obje…