Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Furui Bai"'
Autor:
Marcos V. Conde, Radu Timofte, Yibin Huang, Jingyang Peng, Chang Chen, Cheng Li, Eduardo Pérez-Pellitero, Fenglong Song, Furui Bai, Shuai Liu, Chaoyu Feng, Xiaotao Wang, Lei Lei, Yu Zhu, Chenghua Li, Yingying Jiang, Yong A, Peisong Wang, Cong Leng, Jian Cheng, Xiaoyu Liu, Zhicun Yin, Zhilu Zhang, Junyi Li, Ming Liu, Wangmeng Zuo, Jun Jiang, Jinha Kim, Yue Zhang, Beiji Zou, Zhikai Zong, Xiaoxiao Liu, Juan Marín Vega, Michael Sloth, Peter Schneider-Kamp, Richard Röttger, Furkan Kınlı, Barış Özcan, Furkan Kıraç, Li Leyi, S. M. Nadim Uddin, Dipon Kumar Ghosh, Yong Ju Jung
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250651
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36cb6b4fd46fccc51234f98052decdd7
https://doi.org/10.1007/978-3-031-25066-8_1
https://doi.org/10.1007/978-3-031-25066-8_1
Autor:
Andrey Ignatov, Radu Timofte, Shuai Liu, Chaoyu Feng, Furui Bai, Xiaotao Wang, Lei Lei, Ziyao Yi, Yan Xiang, Zibin Liu, Shaoqing Li, Keming Shi, Dehui Kong, Ke Xu, Minsu Kwon, Yaqi Wu, Jiesi Zheng, Zhihao Fan, Xun Wu, Feng Zhang, Albert No, Minhyeok Cho, Zewen Chen, Xiaze Zhang, Ran Li, Juan Wang, Zhiming Wang, Marcos V. Conde, Ui-Jin Choi, Georgy Perevozchikov, Egor Ershov, Zheng Hui, Mengchuan Dong, Xin Lou, Wei Zhou, Cong Pang, Haina Qin, Mingxuan Cai
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250651
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce2428b1dc386f8189c1811e3767bfa6
https://doi.org/10.1007/978-3-031-25066-8_3
https://doi.org/10.1007/978-3-031-25066-8_3
Autor:
Furkan Kınlı, Sami Menteş, Barış Özcan, Furkan Kıraç, Radu Timofte, Yi Zuo, Zitao Wang, Xiaowen Zhang, Yu Zhu, Chenghua Li, Cong Leng, Jian Cheng, Shuai Liu, Chaoyu Feng, Furui Bai, Xiaotao Wang, Lei Lei, Tianzhi Ma, Zihan Gao, Wenxin He, Woon-Ha Yeo, Wang-Taek Oh, Young-Il Kim, Han-Cheol Ryu, Gang He, Shaoyi Long, S. M. A. Sharif, Rizwan Ali Naqvi, Sungjun Kim, Guisik Kim, Seohyeon Lee, Sabari Nathan, Priya Kansal
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250651
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1fdcd562480bb2102d494ca253932060
https://doi.org/10.1007/978-3-031-25066-8_2
https://doi.org/10.1007/978-3-031-25066-8_2
Publikováno v:
Neurocomputing. 368:25-33
Recently, deep convolutional neural networks (CNNs) with skip-connections in single image super-resolution (SISR) have received great success. However, the difficulty of reconstructing high-resolution images is particularly pronounced for the limited
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d6b8ff2eeed748d336ddb08f277b0af
https://doi.org/10.1016/j.neucom.2019.08.070
https://doi.org/10.1016/j.neucom.2019.08.070
Publikováno v:
VCIP
There are limitations in existing multi-exposure fused image quality assessment (MEF-IQA) approaches. The first is that the existing approaches are hard to estimate the consistency of luminance distribution in fused images, which can be easily destro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4637c70aa9beafac3ffe16792df2741
https://doi.org/10.1109/vcip47243.2019.8966056
https://doi.org/10.1109/vcip47243.2019.8966056
Autor:
Sungil Kang, Tuo Feng, Qinghua Hu, Sai Saketh Chennamsetty, Xudong Wei, Dheeraj Reddy Pailla, Lei Zhang, Keyang Wang, Srinivas S S Kruthiventi, Wei Dai, Hailin Shi, Xiaorui Wang, Almaz Zinollayev, Lars Sommer, Chang Liu, Xin Zhang, Shuhao Chen, Zhikang Wang, Jing Ge, Xinyao Wang, Aijin Li, Zichen Song, DeChun Cong, Jihoon Lee, Jingkai Zhou, Byeongwon Lee, Ziming Liu, Dawei Du, Jonas Meier, Furui Bai, Qingxuan Lv, Donghyeon Cho, Sungeun Hong, Anuar Askergaliyev, Chunlei Huo, Hongliang Li, Haitao Xiong, Xuankun Chen, Tong Wu, Wanqi Li, Kaiqi Huang, Yifu Chen, Aashish Kumar, Weida Qin, Hao Qi, Lianghua Huang, Yunxin Zhong, Ildoo Kim, Jun Won Choi, Junying Huang, Jingjing Xu, Xinyu Zhang, Huchuan Lu, Xindi Zhang, Qiang Chen, Xin Chen, Jiayu Zheng, Qishang Cheng, Changrui Chen, Yue Zhang, Guangyu Gao, Yu Heng Toh, Lin Sun, Lei Jin, Liefeng Bo, Jaekyum Kim, Dening Zeng, Yu Zhang, Xiaoyu Chen, Longyin Wen, Nuo Xu, Haibin Lin, Di Li, Xiao Bian, Xin Zhao, Yu Zhu, Da Yu, Pengyi Zhang, Lucas Steinmann, Guizhong Liu, Varghese Alex Kollerathu, Junhao Hu, Arne Schumann, Pengfei Zhu, Zexin Wang, Weiyang Wang, Dong Wang, Rui Zhu, George Jose, Tao Peng, Qiong Liu, Dongyu Zhang, Haoran Wang, Meixia Jia, Yanchao Li, Junyi Zhang, Xin Sun, Shuo Wei, Xuzhang Zhang, Binjie Mao, Heqian Qiu, Chunhong Pan, Jane Shen
Publikováno v:
ICCV Workshops
Recently, automatic visual data understanding from drone platforms becomes highly demanding. To facilitate the study, the Vision Meets Drone Object Detection in Image Challenge is held the second time in conjunction with the 17-th International Confe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c84b6a87daab3a2cf988bca7039b500
https://doi.org/10.1109/iccvw.2019.00030
https://doi.org/10.1109/iccvw.2019.00030
Publikováno v:
ICIP
Recently, deep convolutional neural networks (CNNs) have been demonstrated excellent performance on single image super-resolution (SISR). However, most deep learning based methods lack the ability to distinguish features in network. For image super-r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::19947dd72b62ebb418393c05a3212ead
https://doi.org/10.1109/icip.2019.8803381
https://doi.org/10.1109/icip.2019.8803381
Publikováno v:
ICME
Recently, the deep convolutional neural network (CNN) has made remarkable progress in single image super resolution(SISR). However, blindly using the residual structure and dense structure to extract features from LR images, can cause the network to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf95d3869c4dc3d09b3c313f14f31459
http://arxiv.org/abs/1907.02843
http://arxiv.org/abs/1907.02843
Autor:
Furui Bai, Jiawei Li, Sun Anshun, Fujie Gao, Yajun Qiu, Lei Liu, Xiumei Wang, Jiye Liu, Jing Liu, Lei Zhang, Jinghui Qin, Sanghoon Yoon, Guoan Cheng, Ruicheng Feng, Zheng Hui, Lin Zha, Li Guo, Dongliang He, Chu-Tak Li, Cuihua Li, Guochen Xie, Jun Yu, Rong Chen, Bowen Li, Shuhang Gu, Wenyi Tang, Shu Zhan, Zhang Yumei, Xiaoyun Jiang, Yanyun Qu, Qingwen He, Pengxu Wei, Ze Pan, Sungho Kim, Pablo Navarrete Michelini, Zhengping Wei, Xuan Xu, Darui Li, Peidong He, Minbeom Kim, Fan Hongfei, Joon-Soo Kim, Liang Lin, Changyeop Shin, Leilei Zhu, Xiang Li, Wangmeng Zuo, Jianrui Cai, Ling Shao, Donghee Son, Qunbo Lv, Yongcheng Jing, Can Zhao, Yi Fu, Yu Qiao, Chung-Chi Tsai, Shilei Wen, Dongwon Park, Xin Li, Zhi-Song Liu, Li-Wen Wang, Yuanfei Huang, Hongzhi Zhang, Jingdong Liu, Xiaotong Luo, Chen Hong, Fahad Shahbaz Khan, Zewei He, Chao Dong, Pengju Liu, Se Young Chun, Zheng Tan, Yanpeng Cao, Joon-Hee Choi, Chao Li, Xiaopeng Sun, Syed Waqas Zamir, Kai Zhang, Hong Cai, Youngjung Kim, Qiuyu Li, Radu Timofte, Ai Matsune, Yukai Shi, Xiao Liu, Wen Lu, Salman H. Khan, Mengyan Li, Wushao Wen, Huaijuan Zang, Mingli Song, Junhyung Kwak, Shang-Chih Chuang, Hanwen Liu, Xinbo Gao, Du Chen, Ding Yukang, Siliang Tang, Aditya Arora, Zhang Wenjie, Lishan Huang, Jinjin Gu, Ruxin wang, Dan Zhu
Publikováno v:
CVPR Workshops
This paper reviewed the 3rd NTIRE challenge on single-image super-resolution (restoration of rich details in a low-resolution image) with a focus on proposed solutions and results. The challenge had 1 track, which was aimed at the real-world single i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::589c30642190fe143e7dd2b60c9e386c
https://doi.org/10.1109/cvprw.2019.00274
https://doi.org/10.1109/cvprw.2019.00274
Publikováno v:
Big Data ISBN: 9789811329210
Big Data (CCF)
Big Data (CCF)
Recently, deep convolutional neural networks (CNNs) in single image super-resolution (SISR) have received excellent performance. However, most deep-learning-based methods do not make full use of low-level features extracted from the original low-reso
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fa3f8093aaa9f26a9cfbdc3e5eab506
https://doi.org/10.1007/978-981-13-2922-7_20
https://doi.org/10.1007/978-981-13-2922-7_20