63 citations · 65 across the 5 of their papers we have counts for
5 papers
PhysMani: Physics-principled 3D World Model for Dynamic Object Manipulation
Peng Yun, Shouwang Huang, Hao Li +3
Manipulating fast and dynamically moving targets in unstructured 3D environments remains challenging for embodied AI. Existing visual-language-action models and world models strugg…
PhysInOne: Visual Physics Learning and Reasoning in One Suite
Siyuan Zhou, Hejun Wang, Hu Cheng +36
We present PhysInOne, a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike existing datasets limited to mere…
Generative Artificial Intelligence in Robotic Manipulation: A Survey
Kun Zhang, Peng Yun, Jun Cen +11
This survey provides a comprehensive review on recent advancements of generative learning models in robotic manipulation, addressing key challenges in the field. Robotic manipulati…
HAPNet: Toward Superior RGB-Thermal Scene Parsing via Hybrid, Asymmetric, and Progressive Heterogeneous Feature Fusion
Jiahang Li, Peng Yun, Yang Xu +5
Data-fusion networks have shown significant promise for RGB-thermal scene parsing. However, the majority of existing studies have relied on symmetric duplex encoders for heterogene…
RoadFormer: Duplex Transformer for RGB-Normal Semantic Road Scene Parsing
Jiahang Li, Yikang Zhang, Peng Yun +3
The recent advancements in deep convolutional neural networks have shown significant promise in the domain of road scene parsing. Nevertheless, the existing works focus primarily o…