Zobrazeno 1 - 10
of 232
pro vyhledávání: '"Longhui Wei"'
Publikováno v:
Multimedia Systems. 29:33-48
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:2642-2650
Recently, contrastive learning has largely advanced the progress of unsupervised visual representation learning. Pre-trained on ImageNet, some self-supervised algorithms reported higher transfer learning performance compared to fully-supervised metho
Publikováno v:
International Journal of Computer Vision. 130:820-835
Autor:
Yang Zijie, Huo Xinyue, Xiaopeng Zhang, Lingxi Xie, Chen Xin, Houqiang Li, Li Hao, Qi Tian, Wengang Zhou, Longhui Wei
Publikováno v:
IEEE Transactions on Multimedia. 24:4224-4235
Unsupervised pretraining is of great significance for visual representation. Especially, contrastive learning has achieved great success recently, but existing approaches mostly ignored spatial information which is often crucial for visual representa
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 32:374-387
Person re-identification (ReID) aims at matching identities across disjoint cameras. Its fundamental difficulty lies in associating images across individual cameras, where a key clue, i.e., identity appearance, is prone to the environmental factors o
Autor:
Longhui WEI1, Binglin LI2, Xiaoli ZHANG2 xlzhang@nwu.edu.cn, Kai TANG1, Wenwen ZHENG1, Dan CHEN1, Binxia ZHAO1
Publikováno v:
Turkish Journal of Chemistry. 2020, Vol. 44 Issue 1, p249-260. 12p.
Autor:
Yongsheng Liang, Jia-Xing Zhong, Qi Tian, Longhui Wei, Xiujun Shu, Ge Li, Xianghao Zang, Shiliang Zhang, Yaowei Wang
Publikováno v:
Pattern Recognition Letters. 149:17-23
Attention mechanisms have achieved success in video-based person re-identification (re-ID). However, current global attentions tend to focus on the most salient parts, e.g., clothes, and ignore other subtle but valuable cues, e.g., hair, bag, and sho
Autor:
LINGXI XIE, XIN CHEN, KAIFENG BI, LONGHUI WEI, YUHUI XU, LANFEI WANG, ZHENGSU CHEN, AN XIAO, JIANLONG CHANG, XIAOPENG ZHANG, QI TIAN
Publikováno v:
ACM Computing Surveys; Dec2022, Vol. 54 Issue 9, p1-37, 37p
Publikováno v:
Comptes Rendus. Chimie. 23:375-384