activity
20232026
most citedNeural Implicit Representation for Building Digital Twins of Unknown Articulated Objects

2 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Geometry-Aware Motion Latents for Learning Robust Manipulation Policies

Yunchao Zhang, Yijia Weng, Ruizhe Liu +3

Learning motion latents for robotic manipulation heavily relies on extracting motion patterns from visual sequences, yet effective action abstractions require understanding three-d…

cs.RO2025

Robot Learning from Any Images

Siheng Zhao, Jiageng Mao, Wei Chow +11

We introduce RoLA, a framework that transforms any in-the-wild image into an interactive, physics-enabled robotic environment. Unlike previous methods, RoLA operates directly on a…

cs.CV2024★ 2 cited

Neural Implicit Representation for Building Digital Twins of Unknown Articulated Objects

Yijia Weng, Bowen Wen, Jonathan Tremblay +4

We address the problem of building digital twins of unknown articulated objects from two RGBD scans of the object at different articulation states. We decompose the problem into tw…

cs.CV2023

Rethinking Directional Integration in Neural Radiance Fields

Congyue Deng, Jiawei Yang, Leonidas Guibas +1

Recent works use the Neural radiance field (NeRF) to perform multi-view 3D reconstruction, providing a significant leap in rendering photorealistic scenes. However, despite its eff…

cs.RO2023★ 2 cited

SparseDFF: Sparse-View Feature Distillation for One-Shot Dexterous Manipulation

Qianxu Wang, Haotong Zhang, Congyue Deng +4

Humans demonstrate remarkable skill in transferring manipulation abilities across objects of varying shapes, poses, and appearances, a capability rooted in their understanding of s…

cs.RO2023

EquivAct: SIM(3)-Equivariant Visuomotor Policies beyond Rigid Object Manipulation

Jingyun Yang, Congyue Deng, Jimmy Wu +3

If a robot masters folding a kitchen towel, we would expect it to master folding a large beach towel. However, existing policy learning methods that rely on data augmentation still…

cs.RO2023

AO-Grasp: Articulated Object Grasp Generation

Carlota Parés Morlans, Claire Chen, Yijia Weng +6

We introduce AO-Grasp, a grasp proposal method that generates 6 DoF grasps that enable robots to interact with articulated objects, such as opening and closing cabinets and applian…