4 citations · 6 across the 4 of their papers we have counts for
4 papers
REGNet V2: End-to-End REgion-based Grasp Detection Network for Grippers of Different Sizes in Point Clouds
Binglei Zhao, Han Wang, Jian Tang +5
Grasping has been a crucial but challenging problem in robotics for many years. One of the most important challenges is how to make grasping generalizable and robust to novel objec…
REGRAD: A Large-Scale Relational Grasp Dataset for Safe and Object-Specific Robotic Grasping in Clutter
Hanbo Zhang, Deyu Yang, Han Wang +4
Despite the impressive progress achieved in robotic grasping, robots are not skilled in sophisticated tasks (e.g. search and grasp a specified target in clutter). Such tasks involv…
TDRE: A Tensor Decomposition Based Approach for Relation Extraction
Bin-Bin Zhao, Liang Li, Hui-Dong Zhang
Extracting entity pairs along with relation types from unstructured texts is a fundamental subtask of information extraction. Most existing joint models rely on fine-grained labeli…
REGNet: REgion-based Grasp Network for End-to-end Grasp Detection in Point Clouds
Binglei Zhao, Hanbo Zhang, Xuguang Lan +3
Reliable robotic grasping in unstructured environments is a crucial but challenging task. The main problem is to generate the optimal grasp of novel objects from partial noisy obse…