5 papers
DynamicVLA: A Vision-Language-Action Model for Dynamic Object Manipulation
Haozhe Xie, Beichen Wen, Jiarui Zheng +4
Manipulating dynamic objects remains an open challenge for Vision-Language-Action (VLA) models, which, despite strong generalization in static manipulation, struggle in dynamic sce…
SPATIALGEN: Layout-guided 3D Indoor Scene Generation
Chuan Fang, Heng Li, Yixun Liang +6
Creating high-fidelity 3D models of indoor environments is essential for applications in design, virtual reality, and robotics. However, manual 3D modeling remains time-consuming a…
SpatialLM: Training Large Language Models for Structured Indoor Modeling
Yongsen Mao, Junhao Zhong, Chuan Fang +5
SpatialLM is a large language model designed to process 3D point cloud data and generate structured 3D scene understanding outputs. These outputs include architectural elements lik…
GLOVER++: Unleashing the Potential of Affordance Learning from Human Behaviors for Robotic Manipulation
Teli Ma, Jia Zheng, Zifan Wang +3
Learning manipulation skills from human demonstration videos offers a promising path toward generalizable and interpretable robotic intelligence-particularly through the lens of ac…
From 2D CAD Drawings to 3D Parametric Models: A Vision-Language Approach
Xilin Wang, Jia Zheng, Yuanchao Hu +3
In this paper, we present CAD2Program, a new method for reconstructing 3D parametric models from 2D CAD drawings. Our proposed method is inspired by recent successes in vision-lang…