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pro vyhledávání: '"Lai, Shenqi"'
Autor:
Zhang, Hao, Xu, Lumin, Lai, Shenqi, Shao, Wenqi, Zheng, Nanning, Luo, Ping, Qiao, Yu, Zhang, Kaipeng
Current image-based keypoint detection methods for animal (including human) bodies and faces are generally divided into full-supervised and few-shot class-agnostic approaches. The former typically relies on laborious and time-consuming manual annotat
Externí odkaz:
http://arxiv.org/abs/2310.05056
Publikováno v:
In Pattern Recognition December 2024 156
Autor:
Fan, Mingyuan, Lai, Shenqi, Huang, Junshi, Wei, Xiaoming, Chai, Zhenhua, Luo, Junfeng, Wei, Xiaolin
BiSeNet has been proved to be a popular two-stream network for real-time segmentation. However, its principle of adding an extra path to encode spatial information is time-consuming, and the backbones borrowed from pretrained tasks, e.g., image class
Externí odkaz:
http://arxiv.org/abs/2104.13188
In this paper, we propose a novel Feature Decomposition and Reconstruction Learning (FDRL) method for effective facial expression recognition. We view the expression information as the combination of the shared information (expression similarities) a
Externí odkaz:
http://arxiv.org/abs/2104.05160
Knowledge distillation (KD) is widely used for training a compact model with the supervision of another large model, which could effectively improve the performance. Previous methods mainly focus on two aspects: 1) training the student to mimic repre
Externí odkaz:
http://arxiv.org/abs/1911.07471
This study explores a simple but strong baseline for person re-identification (ReID). Person ReID with deep neural networks has progressed and achieved high performance in recent years. However, many state-of-the-art methods design complex network st
Externí odkaz:
http://arxiv.org/abs/1906.08332
Autor:
Liu, Yinglu, Shen, Hao, Si, Yue, Wang, Xiaobo, Zhu, Xiangyu, Shi, Hailin, Hong, Zhibin, Guo, Hanqi, Guo, Ziyuan, Chen, Yanqin, Li, Bi, Xi, Teng, Yu, Jun, Xie, Haonian, Xie, Guochen, Li, Mengyan, Lu, Qing, Wang, Zengfu, Lai, Shenqi, Chai, Zhenhua, Wei, Xiaoming
Facial landmark localization is a very crucial step in numerous face related applications, such as face recognition, facial pose estimation, face image synthesis, etc. However, previous competitions on facial landmark localization (i.e., the 300-W, 3
Externí odkaz:
http://arxiv.org/abs/1905.03469
This paper explores a simple and efficient baseline for person re-identification (ReID). Person re-identification (ReID) with deep neural networks has made progress and achieved high performance in recent years. However, many state-of-the-arts method
Externí odkaz:
http://arxiv.org/abs/1903.07071
Akademický článek
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Publikováno v:
In Pattern Recognition November 2022 131