Zobrazeno 1 - 10
of 182
pro vyhledávání: '"Gao, Boyang"'
We focus on the generalization ability of the 6-DoF grasp detection method in this paper. While learning-based grasp detection methods can predict grasp poses for unseen objects using the grasp distribution learned from the training set, they often e
Externí odkaz:
http://arxiv.org/abs/2404.01727
This paper focuses on the sim-to-real issue of RGB-D grasp detection and formulates it as a domain adaptation problem. In this case, we present a global-to-local method to address hybrid domain gaps in RGB and depth data and insufficient multi-modal
Externí odkaz:
http://arxiv.org/abs/2403.11511
Planar grasp detection is one of the most fundamental tasks to robotic manipulation, and the recent progress of consumer-grade RGB-D sensors enables delivering more comprehensive features from both the texture and shape modalities. However, depth map
Externí odkaz:
http://arxiv.org/abs/2302.14264
Autor:
Zou, Hang, Li, Yong, Wang, Haiyao, Yu, Fengzhi, Li, Jiadong, Wang, Yilei, Gao, Boyang, Wang, Yin, Xu, Guangming
Publikováno v:
In Journal of Materials Research and Technology September-October 2024 32:1286-1298
Autor:
Yue, Hangyu, Xu, Xinying, Wang, Yunlou, Miao, Kesong, Peng, Hui, Gao, Boyang, Yang, Jixin, Li, Rengeng, Fan, Guohua
Publikováno v:
In Materials Science & Engineering A September 2024 911
Publikováno v:
Fenmo yejin jishu, Vol 42, Iss 1, Pp 59-67 (2024)
As a new type of functional and structural material, the porous metal materials have been widely used in the fields of sound absorption, energy absorption, fluid distribution, heat exchange, catalysis, filtration, and separation, which are the most w
Externí odkaz:
https://doaj.org/article/4af56b7c12874c0bbd2ff46da24a3335
Autor:
Li, Yanqiang, Yi, Yang, Gao, Xinlei, Wang, Xin, Zhao, Dongyu, Wang, Rui, Zhang, Li-Sheng, Gao, Boyang, Zhang, Yadong, Zhang, Lili, Cao, Qi, Chen, Kaifu
Publikováno v:
In Molecular Cell 20 June 2024 84(12):2320-2336
This paper proposes a new deep learning approach to antipodal grasp detection, named Double-Dot Network (DD-Net). It follows the recent anchor-free object detection framework, which does not depend on empirically pre-set anchors and thus allows more
Externí odkaz:
http://arxiv.org/abs/2108.01527
Autor:
Yue, Hangyu, Wang, Yunlou, Peng, Hui, Miao, Kesong, Liang, Zhenquan, Xu, Lijuan, Xiao, Shulong, Gao, Boyang, Xie, Xinliang, Li, Xuewen, Chao, Qi, Fan, Guohua
Publikováno v:
In Materials Science & Engineering A March 2024 896
Autor:
Bai, Youru, Yu, Xiaochen, Gao, Boyang, Wang, Yajing, Yang, Hanbo, Wu, Chaofei, Wei, Ruru, Guo, Kexuan, Zhao, Peng
Publikováno v:
In Journal of Luminescence February 2024 266