Zobrazeno 1 - 10
of 121
pro vyhledávání: '"Peng, Zhanglin"'
Autor:
Meng, Fanqing, Shao, Wenqi, Peng, Zhanglin, Jiang, Chonghe, Zhang, Kaipeng, Qiao, Yu, Luo, Ping
This paper investigates an under-explored but important problem: given a collection of pre-trained neural networks, predicting their performance on each multi-modal task without fine-tuning them, such as image recognition, referring, captioning, visu
Externí odkaz:
http://arxiv.org/abs/2308.06262
In recent years, the Transformer architecture has shown its superiority in the video-based person re-identification task. Inspired by video representation learning, these methods mainly focus on designing modules to extract informative spatial and te
Externí odkaz:
http://arxiv.org/abs/2301.00531
To further reduce the cost of semi-supervised domain adaptation (SSDA) labeling, a more effective way is to use active learning (AL) to annotate a selected subset with specific properties. However, domain adaptation tasks are always addressed in two
Externí odkaz:
http://arxiv.org/abs/2205.11192
Publikováno v:
In Computers & Industrial Engineering November 2024 197
Publikováno v:
In Advanced Engineering Informatics October 2024 62 Part B
Publikováno v:
In Engineering Applications of Artificial Intelligence January 2025 139 Part A
Autor:
Ignatov, Andrey, Timofte, Radu, Zhang, Zhilu, Liu, Ming, Wang, Haolin, Zuo, Wangmeng, Zhang, Jiawei, Zhang, Ruimao, Peng, Zhanglin, Ren, Sijie, Dai, Linhui, Liu, Xiaohong, Li, Chengqi, Chen, Jun, Ito, Yuichi, Vasudeva, Bhavya, Deora, Puneesh, Pal, Umapada, Guo, Zhenyu, Zhu, Yu, Liang, Tian, Li, Chenghua, Leng, Cong, Pan, Zhihong, Li, Baopu, Kim, Byung-Hoon, Song, Joonyoung, Ye, Jong Chul, Baek, JaeHyun, Zhussip, Magauiya, Koishekenov, Yeskendir, Ye, Hwechul Cho, Liu, Xin, Hu, Xueying, Jiang, Jun, Gu, Jinwei, Li, Kai, Tan, Pengliang, Hou, Bingxin
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to-RGB mapping problem, where to goal was to map the original low-qualit
Externí odkaz:
http://arxiv.org/abs/2011.04994
Normalization techniques are important in different advanced neural networks and different tasks. This work investigates a novel dynamic learning-to-normalize (L2N) problem by proposing Exemplar Normalization (EN), which is able to learn different no
Externí odkaz:
http://arxiv.org/abs/2003.08761
Akademický článek
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Publikováno v:
In Pattern Recognition September 2023 141