1 citations · 2 across the 4 of their papers we have counts for
5 papers
LensDFF: Language-enhanced Sparse Feature Distillation for Efficient Few-Shot Dexterous Manipulation
Qian Feng, David S. Martinez Lema, Jianxiang Feng +2
Learning dexterous manipulation from few-shot demonstrations is a significant yet challenging problem for advanced, human-like robotic systems. Dense distilled feature fields have…
DexGANGrasp: Dexterous Generative Adversarial Grasping Synthesis for Task-Oriented Manipulation
Qian Feng, David S. Martinez Lema, Mohammadhossein Malmir +4
We introduce DexGanGrasp, a dexterous grasping synthesis method that generates and evaluates grasps with single view in real time. DexGanGrasp comprises a Conditional Generative Ad…
FFHFlow: Diverse and Uncertainty-Aware Dexterous Grasp Generation via Flow Variational Inference
Qian Feng, Jianxiang Feng, Zhaopeng Chen +2
Synthesizing diverse, uncertainty-aware grasps for multi-fingered hands from partial observations remains a critical challenge in robot learning. Prior generative methods struggle…
Language-Guided Object-Centric Diffusion Policy for Generalizable and Collision-Aware Robotic Manipulation
Hang Li, Qian Feng, Zhi Zheng +3
Learning from demonstrations faces challenges in generalizing beyond the training data and often lacks collision awareness. This paper introduces Lan-o3dp, a language-guided object…
Multi-fingered Dynamic Grasping for Unknown Objects
Yannick Burkhardt, Qian Feng, Jianxiang Feng +3
Dexterous grasping of unseen objects in dynamic environments is an essential prerequisite for the advanced manipulation of autonomous robots. Prior advances rely on several assumpt…