1 citations · 1 across the 8 of their papers we have counts for
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Learning Action Manifold with Multi-view Latent Priors for Robotic Manipulation
Junjin Xiao, Dongyang Li, Yandan Yang +9
This paper tackles spatial perception and manipulation challenges in Vision-Language-Action (VLA) models. To address depth ambiguity from monocular input, we leverage a pre-trained…
ABot-PhysWorld: Interactive World Foundation Model for Robotic Manipulation with Physics Alignment
Yuzhi Chen, Ronghan Chen, Dongjie Huo +11
Video-based world models offer a powerful paradigm for embodied simulation and planning, yet state-of-the-art models often generate physically implausible manipulations - such as o…
Learning Explicit Continuous Motion Representation for Dynamic Gaussian Splatting from Monocular Videos
Xuankai Zhang, Junjin Xiao, Shangwei Huang +2
We present an approach for high-quality dynamic Gaussian Splatting from monocular videos. To this end, we in this work go one step further beyond previous methods to explicitly mod…
ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning
Yandan Yang, Shuang Zeng, Tong Lin +11
Building general-purpose embodied agents across diverse hardware remains a central challenge in robotics, often framed as the ''one-brain, many-forms'' paradigm. Progress is hinder…