64 citations · 67 across the 7 of their papers we have counts for
9 papers
Let the Mind Conceive, Let the Hand Achieve: Following Multimodal Instructions for Long-Horizon Robotic Manipulation
Youpeng Wen, Gang Wang, Tianyu Huang +5
A robot following a multi-step instruction needs to act on the right objects in the right order, even as the scene changes. It must also maintain awareness of task progress and det…
A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model
Kaidong Zhang, Jian Zhang, Rongtao Xu +20
Vision-Language-Action (VLA) models have emerged as a powerful paradigm for open-world robot manipulation, but their practical deployment is often constrained by cost: billion-scal…
Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI
Kun Xiang, Terry Jingchen Zhang, Yinya Huang +13
The rapid advancement of embodied intelligence and world models has intensified efforts to integrate physical laws into AI systems, yet physical perception and symbolic physics rea…
RoboPearls: Editable Video Simulation for Robot Manipulation
Tao Tang, Likui Zhang, Youpeng Wen +9
The development of generalist robot manipulation policies has seen significant progress, driven by large-scale demonstration data across diverse environments. However, the high cos…
A0: An Affordance-Aware Hierarchical Model for General Robotic Manipulation
Rongtao Xu, Jian Zhang, Minghao Guo +11
Robotic manipulation faces critical challenges in understanding spatial affordances--the "where" and "how" of object interactions--essential for complex manipulation tasks like wip…
VidMan: Exploiting Implicit Dynamics from Video Diffusion Model for Effective Robot Manipulation
Youpeng Wen, Junfan Lin, Yi Zhu +4
Recent advancements utilizing large-scale video data for learning video generation models demonstrate significant potential in understanding complex physical dynamics. It suggests…
CapDet: Unifying Dense Captioning and Open-World Detection Pretraining
Yanxin Long, Youpeng Wen, Jianhua Han +5
Benefiting from large-scale vision-language pre-training on image-text pairs, open-world detection methods have shown superior generalization ability under the zero-shot or few-sho…
DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection
Lewei Yao, Jianhua Han, Youpeng Wen +6
Open-world object detection, as a more general and challenging goal, aims to recognize and localize objects described by arbitrary category names. The recent work GLIP formulates t…
Open-world Semantic Segmentation via Contrasting and Clustering Vision-Language Embedding
Quande Liu, Youpeng Wen, Jianhua Han +3
To bridge the gap between supervised semantic segmentation and real-world applications that acquires one model to recognize arbitrary new concepts, recent zero-shot segmentation at…