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cs.CV2026
VideoAfford: Grounding 3D Affordance from Human-Object-Interaction Videos via Multimodal Large Language Model
Hanqing Wang, Mingyu Liu, Xiaoyu Chen +9
3D affordance grounding aims to highlight the actionable regions on 3D objects, which is crucial for robotic manipulation. Previous research primarily focused on learning affordanc…
cs.CV2025
EvolvingGrasp: Evolutionary Grasp Generation via Efficient Preference Alignment
Yufei Zhu, Yiming Zhong, Zemin Yang +4
Dexterous robotic hands often struggle to generalize effectively in complex environments due to the limitations of models trained on low-diversity data. However, the real world pre…
cs.CV2025
DexGrasp Anything: Towards Universal Robotic Dexterous Grasping with Physics Awareness
Yiming Zhong, Qi Jiang, Jingyi Yu +1
A dexterous hand capable of grasping any object is essential for the development of general-purpose embodied intelligent robots. However, due to the high degree of freedom in dexte…