Yinghao Shuai — accepted AI-conference papers

2025

PUGS: Zero-Shot Physical Understanding with Gaussian Splatting

Yinghao Shuai, Ran Yu, Yuantao Chen, Zijian Jiang, Xiaowei Song, Nan Wang +6

ICRA 2025

Current robotic systems can understand the categories and poses of objects well. But understanding physical properties like mass, friction, and hardness, in the wild, remains challenging. We propose a new method that reconstructs 3D objects using the Gaussian splatting representation and predicts va

Cited by 11 Source ↗code ↗Scholar ↗

2025

RE0: Recognize Everything with 3D Zero-Shot Instance Segmentation

Xiaohan Yan, Zijian Jiang, Yinghao Shuai, Nan Wang, Xiaowei Song, Wenbo Ji +4

ICRA 2025

Recognizing objects in the 3D world is a significant challenge for robotics. Due to the lack of high-quality 3D data, directly training a general-purpose segmentation model in 3D is almost infeasible. Meanwhile, vision foundation models (VFM) have revolutionized the 2D computer vision field with out

Cited by 1 Source ↗code ↗Scholar ↗