45 citations · 333 across the 23 of their papers we have counts for
6 papers · 1 filter
RoboAssembly: Learning Generalizable Furniture Assembly Policy in a Novel Multi-robot Contact-rich Simulation Environment
Mingxin Yu, Lin Shao, Zhehuan Chen +4
Part assembly is a typical but challenging task in robotics, where robots assemble a set of individual parts into a complete shape. In this paper, we develop a robotic assembly sim…
AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-shot Interactions
Yian Wang, Ruihai Wu, Kaichun Mo +4
Perceiving and interacting with 3D articulated objects, such as cabinets, doors, and faucets, pose particular challenges for future home-assistant robots performing daily tasks in…
ADeLA: Automatic Dense Labeling with Attention for Viewpoint Adaptation in Semantic Segmentation
Yanchao Yang, Hanxiang Ren, He Wang +5
We describe an unsupervised domain adaptation method for image content shift caused by viewpoint changes for a semantic segmentation task. Most existing methods perform domain alig…
Contrastive Multimodal Fusion with TupleInfoNCE
Yunze Liu, Qingnan Fan, Shanghang Zhang +3
This paper proposes a method for representation learning of multimodal data using contrastive losses. A traditional approach is to contrast different modalities to learn the inform…
VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects
Ruihai Wu, Yan Zhao, Kaichun Mo +7
Perceiving and manipulating 3D articulated objects (e.g., cabinets, doors) in human environments is an important yet challenging task for future home-assistant robots. The space of…
CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds
Yijia Weng, He Wang, Qiang Zhou +6
In this work, we tackle the problem of category-level online pose tracking of objects from point cloud sequences. For the first time, we propose a unified framework that can handle…