Zobrazeno 1 - 10
of 116
pro vyhledávání: '"Chen, Yuanpei"'
Can we endow visuomotor robots with generalization capabilities to operate in diverse open-world scenarios? In this paper, we propose \textbf{Maniwhere}, a generalizable framework tailored for visual reinforcement learning, enabling the trained robot
Externí odkaz:
http://arxiv.org/abs/2407.15815
Autor:
Fu, Ying, Li, Yu, You, Shaodi, Shi, Boxin, Chen, Linwei, Zou, Yunhao, Wang, Zichun, Li, Yichen, Han, Yuze, Zhang, Yingkai, Wang, Jianan, Liu, Qinglin, Yu, Wei, Lv, Xiaoqian, Li, Jianing, Zhang, Shengping, Ji, Xiangyang, Chen, Yuanpei, Zhang, Yuhan, Peng, Weihang, Zhang, Liwen, Xu, Zhe, Gou, Dingyong, Li, Cong, Xu, Senyan, Zhang, Yunkang, Jiang, Siyuan, Lu, Xiaoqiang, Jiao, Licheng, Liu, Fang, Liu, Xu, Li, Lingling, Ma, Wenping, Yang, Shuyuan, Xie, Haiyang, Zhao, Jian, Huang, Shihua, Cheng, Peng, Shen, Xi, Wang, Zheng, An, Shuai, Zhu, Caizhi, Li, Xuelong, Zhang, Tao, Li, Liang, Liu, Yu, Yan, Chenggang, Zhang, Gengchen, Jiang, Linyan, Song, Bingyi, An, Zhuoyu, Lei, Haibo, Luo, Qing, Song, Jie, Liu, Yuan, Li, Qihang, Zhang, Haoyuan, Wang, Lingfeng, Chen, Wei, Luo, Aling, Li, Cheng, Cao, Jun, Chen, Shu, Dou, Zifei, Liu, Xinyu, Zhang, Jing, Zhang, Kexin, Yang, Yuting, Gou, Xuejian, Wang, Qinliang, Liu, Yang, Zhao, Shizhan, Zhang, Yanzhao, Yan, Libo, Guo, Yuwei, Li, Guoxin, Gao, Qiong, Che, Chenyue, Sun, Long, Chen, Xiang, Li, Hao, Pan, Jinshan, Xie, Chuanlong, Chen, Hongming, Li, Mingrui, Deng, Tianchen, Huang, Jingwei, Li, Yufeng, Wan, Fei, Xu, Bingxin, Cheng, Jian, Liu, Hongzhe, Xu, Cheng, Zou, Yuxiang, Pan, Weiguo, Dai, Songyin, Jia, Sen, Zhang, Junpei, Chen, Puhua
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to inform and enhance deep learning models, we can develop more robust and ac
Externí odkaz:
http://arxiv.org/abs/2406.10744
Autor:
Guo, Yufei, Chen, Yuanpei
The Spiking Neural Network (SNN) is a biologically inspired neural network infrastructure that has recently garnered significant attention. It utilizes binary spike activations to transmit information, thereby replacing multiplications with additions
Externí odkaz:
http://arxiv.org/abs/2401.04486
The Spiking Neural Network (SNN), as one of the biologically inspired neural network infrastructures, has drawn increasing attention recently. It adopts binary spike activations to transmit information, thus the multiplications of activations and wei
Externí odkaz:
http://arxiv.org/abs/2312.06372
Recently, Spiking Neural Networks (SNNs), enjoying extreme energy efficiency, have drawn much research attention on 2D visual recognition and shown gradually increasing application potential. However, it still remains underexplored whether SNNs can b
Externí odkaz:
http://arxiv.org/abs/2310.06232
Autor:
Huang, Binghao, Chen, Yuanpei, Wang, Tianyu, Qin, Yuzhe, Yang, Yaodong, Atanasov, Nikolay, Wang, Xiaolong
Humans throw and catch objects all the time. However, such a seemingly common skill introduces a lot of challenges for robots to achieve: The robots need to operate such dynamic actions at high-speed, collaborate precisely, and interact with diverse
Externí odkaz:
http://arxiv.org/abs/2309.05655
Many real-world manipulation tasks consist of a series of subtasks that are significantly different from one another. Such long-horizon, complex tasks highlight the potential of dexterous hands, which possess adaptability and versatility, capable of
Externí odkaz:
http://arxiv.org/abs/2309.00987
Autor:
Guo, Yufei, Zhang, Yuhan, Chen, Yuanpei, Peng, Weihang, Liu, Xiaode, Zhang, Liwen, Huang, Xuhui, Ma, Zhe
As one of the energy-efficient alternatives of conventional neural networks (CNNs), spiking neural networks (SNNs) have gained more and more interest recently. To train the deep models, some effective batch normalization (BN) techniques are proposed
Externí odkaz:
http://arxiv.org/abs/2308.08359
Autor:
Guo, Yufei, Liu, Xiaode, Chen, Yuanpei, Zhang, Liwen, Peng, Weihang, Zhang, Yuhan, Huang, Xuhui, Ma, Zhe
Spiking Neural Networks (SNNs) as one of the biology-inspired models have received much attention recently. It can significantly reduce energy consumption since they quantize the real-valued membrane potentials to 0/1 spikes to transmit information t
Externí odkaz:
http://arxiv.org/abs/2308.06787
Autor:
Guo, Yufei, Chen, Yuanpei, Zhang, Liwen, Liu, Xiaode, Tong, Xinyi, Ou, Yuanyuan, Huang, Xuhui, Ma, Zhe
The Spiking Neural Network (SNN) has attracted more and more attention recently. It adopts binary spike signals to transmit information. Benefitting from the information passing paradigm of SNNs, the multiplications of activations and weights can be
Externí odkaz:
http://arxiv.org/abs/2307.04356