2.9k citations · 3.1k across the 32 of their papers we have counts for
5 papers · 1 filter
Towards Learning Geometric Eigen-Lengths Crucial for Fitting Tasks
Yijia Weng, Kaichun Mo, Ruoxi Shi +2
Some extremely low-dimensional yet crucial geometric eigen-lengths often determine the success of some geometric tasks. For example, the height of an object is important to measure…
JacobiNeRF: NeRF Shaping with Mutual Information Gradients
Xiaomeng Xu, Yanchao Yang, Kaichun Mo +3
We propose a method that trains a neural radiance field (NeRF) to encode not only the appearance of the scene but also semantic correlations between scene points, regions, or entit…
Category-Level Multi-Part Multi-Joint 3D Shape Assembly
Yichen Li, Kaichun Mo, Yueqi Duan +5
Shape assembly composes complex shapes geometries by arranging simple part geometries and has wide applications in autonomous robotic assembly and CAD modeling. Existing works focu…
Learning Language-Conditioned Deformable Object Manipulation with Graph Dynamics
Yuhong Deng, Kai Mo, Chongkun Xia +1
Multi-task learning of deformable object manipulation is a challenging problem in robot manipulation. Most previous works address this problem in a goal-conditioned way and adapt g…
SceneHGN: Hierarchical Graph Networks for 3D Indoor Scene Generation with Fine-Grained Geometry
Lin Gao, Jia-Mu Sun, Kaichun Mo +3
3D indoor scenes are widely used in computer graphics, with applications ranging from interior design to gaming to virtual and augmented reality. They also contain rich information…