2 citations · 4 across the 7 of their papers we have counts for
4 papers · 2 filters
GAPartManip: A Large-scale Part-centric Dataset for Material-Agnostic Articulated Object Manipulation
Wenbo Cui, Chengyang Zhao, Songlin Wei +5
Effectively manipulating articulated objects in household scenarios is a crucial step toward achieving general embodied artificial intelligence. Mainstream research in 3D vision ha…
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…
D3RoMa: Disparity Diffusion-based Depth Sensing for Material-Agnostic Robotic Manipulation
Songlin Wei, Haoran Geng, Jiayi Chen +6
Depth sensing is an important problem for 3D vision-based robotics. Yet, a real-world active stereo or ToF depth camera often produces noisy and incomplete depth which bottlenecks…
RAM: Retrieval-Based Affordance Transfer for Generalizable Zero-Shot Robotic Manipulation
Yuxuan Kuang, Junjie Ye, Haoran Geng +5
This work proposes a retrieve-and-transfer framework for zero-shot robotic manipulation, dubbed RAM, featuring generalizability across various objects, environments, and embodiment…