Zobrazeno 1 - 10
of 255
pro vyhledávání: '"Wen, Junjie"'
Autor:
Wu, Kun, Zhu, Yichen, Li, Jinming, Wen, Junjie, Liu, Ning, Xu, Zhiyuan, Qiu, Qinru, Tang, Jian
Learning visuomotor policy for multi-task robotic manipulation has been a long-standing challenge for the robotics community. The difficulty lies in the diversity of action space: typically, a goal can be accomplished in multiple ways, resulting in a
Externí odkaz:
http://arxiv.org/abs/2409.18707
Autor:
Zhu, Minjie, Zhu, Yichen, Li, Jinming, Wen, Junjie, Xu, Zhiyuan, Liu, Ning, Cheng, Ran, Shen, Chaomin, Peng, Yaxin, Feng, Feifei, Tang, Jian
Diffusion Policy is a powerful technique tool for learning end-to-end visuomotor robot control. It is expected that Diffusion Policy possesses scalability, a key attribute for deep neural networks, typically suggesting that increasing model size woul
Externí odkaz:
http://arxiv.org/abs/2409.14411
Autor:
Wen, Junjie, Zhu, Yichen, Li, Jinming, Zhu, Minjie, Wu, Kun, Xu, Zhiyuan, Liu, Ning, Cheng, Ran, Shen, Chaomin, Peng, Yaxin, Feng, Feifei, Tang, Jian
Vision-Language-Action (VLA) models have shown remarkable potential in visuomotor control and instruction comprehension through end-to-end learning processes. However, current VLA models face significant challenges: they are slow during inference and
Externí odkaz:
http://arxiv.org/abs/2409.12514
In recent years, significant progress has been made in the field of underwater image enhancement (UIE). However, its practical utility for high-level vision tasks, such as underwater object detection (UOD) in Autonomous Underwater Vehicles (AUVs), re
Externí odkaz:
http://arxiv.org/abs/2403.19079
While the exploration for embodied AI has spanned multiple decades, it remains a persistent challenge to endow agents with human-level intelligence, including perception, learning, reasoning, decision-making, control, and generalization capabilities,
Externí odkaz:
http://arxiv.org/abs/2402.02385
Autor:
Zhu, Minjie, Zhu, Yichen, Li, Jinming, Wen, Junjie, Xu, Zhiyuan, Che, Zhengping, Shen, Chaomin, Peng, Yaxin, Liu, Dong, Feng, Feifei, Tang, Jian
The language-conditioned robotic manipulation aims to transfer natural language instructions into executable actions, from simple pick-and-place to tasks requiring intent recognition and visual reasoning. Inspired by the dual process theory in cognit
Externí odkaz:
http://arxiv.org/abs/2401.04181
Autor:
Wen, Junjie, Zhu, Yichen, Zhu, Minjie, Li, Jinming, Xu, Zhiyuan, Che, Zhengping, Shen, Chaomin, Peng, Yaxin, Liu, Dong, Feng, Feifei, Tang, Jian
Humans interpret scenes by recognizing both the identities and positions of objects in their observations. For a robot to perform tasks such as \enquote{pick and place}, understanding both what the objects are and where they are located is crucial. W
Externí odkaz:
http://arxiv.org/abs/2401.02814
Autor:
Wen, Junjie
We introduce a finite element method with high-order accuracy for approximating the Vlasov-Poisson system. This method uses continuous Lagrange polynomials as basis functions and employs explicit Runge-Kutta schemes for time discretization. A residua
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-506439
Underwater image enhancement (UIE) is vital for high-level vision-related underwater tasks. Although learning-based UIE methods have made remarkable achievements in recent years, it's still challenging for them to consistently deal with various under
Externí odkaz:
http://arxiv.org/abs/2302.08269
Autor:
Wang, Zhihao, Lin, Zongyu, Liu, Peiqi, ZHeng, Guidong, Wen, Junjie, Chen, Xianxin, Chen, Yujun, Yang, Zhilin
Label noise is ubiquitous in various machine learning scenarios such as self-labeling with model predictions and erroneous data annotation. Many existing approaches are based on heuristics such as sample losses, which might not be flexible enough to
Externí odkaz:
http://arxiv.org/abs/2212.13767