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The 3D Mirage: Probing and Taming 3D Hallucinations
Hoang Nguyen, Xiaohao Xu, Xiaonan Huang
Monocular depth foundation models achieve remarkable generalization by learning large-scale semantic priors, but this creates a critical vulnerability: they hallucinate illusory 3D…
Whole-Body Proprioceptive Morphing: A Modular Soft Gripper for Robust Cross-Scale Grasping
Dong Heon Han, Xiaohao Xu, Yuxi Chen +5
Biological systems, such as the octopus, exhibit masterful cross-scale manipulation by adaptively reconfiguring their entire form, a capability that remains elusive in robotics. Co…
Visual Anomaly Detection under Complex View-Illumination Interplay: A Large-Scale Benchmark
Yunkang Cao, Yuqi Cheng, Xiaohao Xu +6
The practical deployment of Visual Anomaly Detection (VAD) systems is hindered by their sensitivity to real-world imaging variations, particularly the complex interplay between vie…
ViSA-Flow: Accelerating Robot Skill Learning via Large-Scale Video Semantic Action Flow
Changhe Chen, Quantao Yang, Xiaohao Xu +2
One of the central challenges preventing robots from acquiring complex manipulation skills is the prohibitive cost of collecting large-scale robot demonstrations. In contrast, huma…
Towards Ambiguity-Free Spatial Foundation Model: Rethinking and Decoupling Depth Ambiguity
Xiaohao Xu, Feng Xue, Xiang Li +5
Depth ambiguity is a fundamental challenge in spatial scene understanding, especially in transparent scenes where single-depth estimates fail to capture full 3D structure. Existing…
Natural Selection via Foundation Models for Soft Robot Evolution
Changhe Chen, Xiaohao Xu, Xiangdong Wang +1
Designing soft robots is a complex and iterative process that demands cross-disciplinary expertise in materials science, mechanics, and control, often relying on intuition and exte…
Scalable Benchmarking and Robust Learning for Noise-Free Ego-Motion and 3D Reconstruction from Noisy Video
Xiaohao Xu, Tianyi Zhang, Shibo Zhao +8
We aim to redefine robust ego-motion estimation and photorealistic 3D reconstruction by addressing a critical limitation: the reliance on noise-free data in existing models. While…