1 citations · 1 across the 7 of their papers we have counts for
7 papers
APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
Kechun Xu, Zhenjie Zhu, Anzhe Chen +2
Vision-Language-Action (VLA) models that couple pretrained Vision-Language Models (VLMs) with continuous action experts have achieved strong manipulation performance, yet generaliz…
D-REX: Differentiable Real-to-Sim-to-Real Engine for Learning Dexterous Grasping
Haozhe Lou, Mingtong Zhang, Haoran Geng +9
Simulation provides a cost-effective and flexible platform for data generation and policy learning to develop robotic systems. However, bridging the gap between simulation and real…
Seeing to Act, Prompting to Specify: A Bayesian Factorization of Vision Language Action Policy
Kechun Xu, Zhenjie Zhu, Anzhe Chen +7
The pursuit of out-of-distribution generalization in Vision-Language-Action (VLA) models is often hindered by catastrophic forgetting of the Vision-Language Model (VLM) backbone du…
Grounding 3D Object Affordance with Language Instructions, Visual Observations and Interactions
He Zhu, Quyu Kong, Kechun Xu +5
Grounding 3D object affordance is a task that locates objects in 3D space where they can be manipulated, which links perception and action for embodied intelligence. For example, f…
Efficient Alignment of Unconditioned Action Prior for Language-conditioned Pick and Place in Clutter
Kechun Xu, Xunlong Xia, Kaixuan Wang +6
We study the task of language-conditioned pick and place in clutter, where a robot should grasp a target object in open clutter and move it to a specified place. Some approaches le…
Grasp, See, and Place: Efficient Unknown Object Rearrangement with Policy Structure Prior
Kechun Xu, Zhongxiang Zhou, Jun Wu +3
We focus on the task of unknown object rearrangement, where a robot is supposed to re-configure the objects into a desired goal configuration specified by an RGB-D image. Recent wo…
DORec: Decomposed Object Reconstruction and Segmentation Utilizing 2D Self-Supervised Features
Jun Wu, Sicheng Li, Sihui Ji +4
Recovering 3D geometry and textures of individual objects is crucial for many robotics applications, such as manipulation, pose estimation, and autonomous driving. However, decompo…