5 citations · 8 across the 2 of their papers we have counts for
2 papers
cs.RO2020★ 3 cited
Transferable Active Grasping and Real Embodied Dataset
Xiangyu Chen, Zelin Ye, Jiankai Sun +4
Grasping in cluttered scenes is challenging for robot vision systems, as detection accuracy can be hindered by partial occlusion of objects. We adopt a reinforcement learning (RL)…
cs.CV2020★ 5 cited
GraspNet: A Large-Scale Clustered and Densely Annotated Dataset for Object Grasping
Hao-Shu Fang, Chenxi Wang, Minghao Gou +1
Object grasping is critical for many applications, which is also a challenging computer vision problem. However, for the clustered scene, current researches suffer from the problem…