Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Magauiya, Zhussip"'
Autor:
Yang, Ren, Timofte, Radu, Zheng, Meisong, Xing, Qunliang, Qiao, Minglang, Xu, Mai, Jiang, Lai, Liu, Huaida, Chen, Ying, Ben, Youcheng, Zhou, Xiao, Fu, Chen, Cheng, Pei, Yu, Gang, Li, Junyi, Wu, Renlong, Zhang, Zhilu, Shang, Wei, Lv, Zhengyao, Chen, Yunjin, Zhou, Mingcai, Ren, Dongwei, Zhang, Kai, Zuo, Wangmeng, Ostyakov, Pavel, Dmitry, Vyal, Soltanayev, Shakarim, Sergey, Chervontsev, Magauiya, Zhussip, Zou, Xueyi, Yan, Youliang, Michelini, Pablo Navarrete, Lu, Yunhua, Zhang, Diankai, Liu, Shaoli, Gao, Si, Wu, Biao, Zheng, Chengjian, Zhang, Xiaofeng, Lu, Kaidi, Wang, Ning, Canh, Thuong Nguyen, Bach, Thong, Wang, Qing, Sun, Xiaopeng, Ma, Haoyu, Zhao, Shijie, Li, Junlin, Xie, Liangbin, Shi, Shuwei, Yang, Yujiu, Wang, Xintao, Gu, Jinjin, Dong, Chao, Shi, Xiaodi, Nian, Chunmei, Jiang, Dong, Lin, Jucai, Xie, Zhihuai, Ye, Mao, Luo, Dengyan, Peng, Liuhan, Chen, Shengjie, Liu, Xin, Wang, Qian, Liang, Boyang, Dong, Hang, Huang, Yuhao, Chen, Kai, Guo, Xingbei, Sun, Yujing, Wu, Huilei, Wei, Pengxu, Huang, Yulin, Chen, Junying, Lee, Ik Hyun, Khowaja, Sunder Ali, Yoon, Jiseok
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the LDV dataset (240 videos) and 95 additional videos. This challenge incl
Externí odkaz:
http://arxiv.org/abs/2204.09314
Autor:
Ren Yang, Radu Timofte, Xin Li, Qi Zhang, Lin Zhang, Fanglong Liu, Dongliang He, Fu Li, He Zheng, Weihang Yuan, Pavel Ostyakov, Dmitry Vyal, Magauiya Zhussip, Xueyi Zou, Youliang Yan, Lei Li, Jingzhu Tang, Ming Chen, Shijie Zhao, Yu Zhu, Xiaoran Qin, Chenghua Li, Cong Leng, Jian Cheng, Claudio Rota, Marco Buzzelli, Simone Bianco, Raimondo Schettini, Dafeng Zhang, Feiyu Huang, Shizhuo Liu, Xiaobing Wang, Zhezhu Jin, Bingchen Li, Mingxi Li, Ding Liu, Wenbin Zou, Peijie Dong, Tian Ye, Yunchen Zhang, Ming Tan, Xin Niu, Mustafa Ayazoglu, Marcos Conde, Ui-Jin Choi, Zhuang Jia, Tianyu Xu, Yijian Zhang, Mao Ye, Dengyan Luo, Xiaofeng Pan, Liuhan Peng
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250651
This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compressed image, and Track 2 targets the super-resolution of compressed video
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35313e10b1a9e623a89649e3289acbbc
https://doi.org/10.1007/978-3-031-25066-8_8
https://doi.org/10.1007/978-3-031-25066-8_8
Autor:
Goutam Bhat, Martin Danelljan, Radu Timofte, Yizhen Cao, Yuntian Cao, Meiya Chen, Xihao Chen, Shen Cheng, Akshay Dudhane, Haoqiang Fan, Ruipeng Gang, Jian Gao, Yan Gu, Jie Huang, Liufeng Huang, Youngsu Jo, Sukju Kang, Salman Khan, Fahad Shahbaz Khan, Yuki Kondo, Chenghua Li, Fangya Li, Jinjing Li, Youwei Li, Zechao Li, Chenming Liu, Shuaicheng Liu, Zikun Liu, Zhuoming Liu, Ziwei Luo, Zhengxiong Luo, Nancy Mehta, Subrahmanyam Murala, Yoonchan Nam, Chihiro Nakatani, Pavel Ostyakov, Jinshan Pan, Ge Song, Jian Sun, Long Sun, Jinhui Tang, Norimichi Ukita, Zhihong Wen, Qi Wu, Xiaohe Wu, Zeyu Xiao, Zhiwei Xiong, Rongjian Xu, Ruikang Xu, Youliang Yan, Jialin Yang, Wentao Yang, Zhongbao Yang, Fuma Yasue, Mingde Yao, Lei Yu, Cong Zhang, Syed Waqas Zamir, Jianxing Zhang, Shuohao Zhang, Zhilu Zhang, Qian Zheng, Gaofeng Zhou, Magauiya Zhussip, Xueyi Zou, Wangmeng Zuo
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
Autor:
Magauiya Zhussip, Julien Mairal, Ziwei Luo, Christian Micheloni, Haoqiang Fan, Sanghyeok Son, Jean Ponce, Rao Muhammad, Ziluan Liu, Kazutoshi Akita, Xuan Mo, Umer Youliang Yan, Pavel Ostyakov, Youwei Li, Martin Danelljan, Norimichi Ukita, Bruno Lecouat, Lei Yu, Xueyi Zou, Goutam Bhat, Radu Timofte, Shuaicheng Liu, Dae-Shik Kim, Jian Sun, Lanpeng Jia, Wooyeong Cho, Takahiro Maeda, Takeru Oba
Publikováno v:
CVPR Workshops
This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times higher resolution. The challenge contained two tracks; Track 1 evaluating
Autor:
Kyeongha Rho, Qiong Yan, Marcin Mozejko, Jong Hyun Kim, Abdelrahman Abdelhamed, Kyungmin Song, Ioannis Marras, Youliang Yan, Matteo Maggioni, Yunhua Lu, Jiye Liu, Songhyun Yu, Krzysztof Trojanowski, Gregory G. Slabaugh, Pengliang Tang, Wei Liu, Xiaoling Zhang, Han Junyu, Jaayeon Lee, Gang Zhang, Sungho Kim, Yanhong Wu, Yuzhi Zhao, Zhangyu Ye, Tingniao Wang, Wonjin Kim, Yaqi Wu, Bumjun Park, Shusong Xu, Lukasz Treszczotko, Yunchao Zhang, Xiaomu Lu, Jingtuo Liu, Yanwen Fan, Zengli Yang, Yue Cao, Thomas Tanay, Xiyu Yu, Wangmeng Zuo, Tomasz Latkowski, Teng Xi, Sabari Nathan, Chenghua Li, Siliang Tang, Sujin Kim, Magauiya Zhussip, Xiwen Lu, Changyeop Shin, Fengshuo Hu, Yanpeng Cao, Michal Szafraniuk, Jechang Jeong, Jiangxin Yang, Mahmoud Afifi, Baopu Li, Ziyao Zong, Shuangquan Wang, Zhilu Zhang, Bin Liu, Jungwon Lee, Nan Nan, Youngjung Kim, Zhihao Li, Rajat Gupta, Shuailin Lv, Nisarg A. Shah, Hwechul Cho, Radu Timofte, Changyuan Wen, Yanlong Cao, Thomas S. Huang, Azamat Khassenov, Wendong Chen, Myungjoo Kang, Long Bao, Yuchen Fan, Dongwoon Bai, Yuqian Zhou, Jang-Hwan Choi, Pablo Navarrete Michelini, Meng Liu, Yiyun Zhao, Vineet Kumar, Michael S. Brown, Chunxia Lei, Zhihong Pan, Han-Soo Choi, Shuai Liu, Errui Ding, Priya Kansal
Publikováno v:
CVPR Workshops
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new version of the previous NTIRE 2019 challenge on real image denoising that w
Autor:
Zhihong Pan, Magauiya Zhussip, Jun Jiang, Yu Zhu, Umapada Pal, Yeskendir Koishekenov, Joonyoung Song, Ming Liu, Jinwei Gu, Jun Chen, Chengqi Li, Xin Liu, Xiaohong Liu, Pengliang Tan, Bingxin Hou, Linhui Dai, Bhavya Vasudeva, Jiawei Zhang, Byung-Hoon Kim, Radu Timofte, JaeHyun Baek, Kai Li, Chenghua Li, Sijie Ren, Andrey Ignatov, Puneesh Deora, Haolin Wang, Xueying Hu, Tian Liang, Zhenyu Guo, Cong Leng, Hwechul Cho Ye, Wangmeng Zuo, Baopu Li, Zhilu Zhang, Zhanglin Peng, Yuichi Ito, Jong Chul Ye, Ruimao Zhang
Publikováno v:
Computer Vision – ECCV 2020 Workshops ISBN: 9783030670696
ECCV Workshops (3)
ECCV Workshops (3)
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:
https://explore.openaire.eu/search/publication?articleId=doi_________::b79e2bbabe78ef8142c0a391ab7709f3
https://doi.org/10.1007/978-3-030-67070-2_9
https://doi.org/10.1007/978-3-030-67070-2_9
Autor:
Kazutoshi Akita, Thomas S. Huang, Simone Zini, Raimondo Schettini, Jae-Ryun Chung, Bumjun Park, Chuan Wang, Sang-Won Lee, Seung-Won Jung, Simone Bianco, Lei Zhang, Yiyun Zhao, Yuchen Fan, Yifan Ding, Greg Shakhnarovich, Se Young Chun, Hongwei Yong, Ling Shao, Deyu Meng, Wangmeng Zuo, Chi Li, Salman Khan, Tomoki Yoshida, Chang Chen, Ding Liu, Dongwon Park, Wenyi Tang, Zhiwei Xiong, Syed Waqas Zamir, Yuqian Zhou, Norimichi Ukita, Haoqiang Fan, Seung-Wook Kim, Jue Wang, Zhiguo Cao, Yuzhi Wang, Radu Timofte, Dong-Wook Kim, Sung-Jea Ko, Fahad Shahbaz Khan, Magauiya Zhussip, Dong-Pan Lim, Seo-Won Ji, Yang Wang, Muhammad Haris, Aditya Arora, Michael S. Brown, Shakarim Soltanayev, Jiaming Liu, Qin Xu, Abdelrahman Abdelhamed, Shaofan Cai, Kai Zhang, Jechang Jeong, Chi-Hao Wu, Songhyun Yu, Yue Lu, Pengliang Tang
Publikováno v:
CVPR Workshops
This paper reviews the NTIRE 2019 challenge on real image denoising with focus on the proposed methods and their results. The challenge has two tracks for quantitatively evaluating image denoising performance in (1) the Bayer-pattern raw-RGB and (2)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db78361616a907db66c80fa58d06f652
http://hdl.handle.net/10281/274007
http://hdl.handle.net/10281/274007
Publikováno v:
CVPR
Compressive sensing is a method to recover the original image from undersampled measurements. In order to overcome the ill-posedness of this inverse problem, image priors are used such as sparsity in the wavelet domain, minimum total-variation, or se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb34154eccb355869c8cabc715f64afe
Autor:
Ratbek Zhapparov, Magauiya Zhussip
Publikováno v:
Advances in Memristor Circuits and Bioinspired Systems.