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Your search keyword '"Shuhang Gu"' showing total 2 results
Start Over Author "Shuhang Gu" Journal 2019 ieee/cvf conference on computer vision and pattern recognition workshops (cvprw)
2 results on '"Shuhang Gu"'

1. NTIRE 2019 Challenge on Real Image Super-Resolution: Methods and Results

Author

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, and Dan Zhu

Subjects
business.industry, Computer science, Track (disk drive), ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020206 networking & telecommunications, 02 engineering and technology, Real image, Scale factor, Superresolution, Image (mathematics), 0202 electrical engineering, electronic engineering, information engineering, Focal length, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Focus (optics), Image resolution, Image restoration
Abstract

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 image super-resolution problem with an unknown scaling factor. Participants were mapping low-resolution images captured by a DSLR camera with a shorter focal length to their high-resolution images captured at a longer focal length. With this challenge, we introduced a novel real-world super-resolution dataset (RealSR). The track had 403 registered participants, and 36 teams competed in the final testing phase. They gauge the state-of-the-art in real-world single image super-resolution.

Published
2019
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2. NTIRE 2019 Challenge on Video Super-Resolution: Methods and Results

Author

Shuhang Gu, Greg Shakhnarovich, Fatih Porikli, Kyoung Mu Lee, Zhongyuan Wang, Yulun Zhang, Seokil Hong, M. Akin Yilmaz, Kuldeep Purohit, Si Miao, A. S. Mandal, Yapeng Tian, A. Murat Tekalp, Norimichi Ukita, Sanghyun Son, Junjun Jiang, Yun Fu, A.N. Rajagopalan, Chenliang Xu, Gyeongsik Moon, Sungyong Baik, Ankit Shukla, Zhe Hu, Chen Change Loy, Manoj Sharma, Chao Li, Ding Yukang, Dong Un Kang, Yongxin Zhu, Santanu Chaudhury, Ratheesh Kalarot, Hang Dong, Avinash Upadhyay, Muhammad Haris, Ke Yu, Thomas S. Huang, Megh Makwana, Wang Xintao, Xinyi Zhang, Peng Yi, Jiahui Yu, Kwanyoung Kim, Kui Jiang, Chao Dong, Xiao Huo, Rudrabha Mukhopadhyay, Yuchen Fan, Dongliang He, Ding Liu, Se Young Chun, Shilei Wen, Ajay Pratap Singh, Xiao Liu, Kelvin C.K. Chan, Cansu Korkmaz, Jiayi Ma, Radu Timofte, Anuj Badhwar, Seungjun Nah, Dheeraj Khanna, Tekalp, Ahmet Murat (ORCID 0000-0003-1465-8121 & YÖK ID 26207), Nah, S., Timofte, R., Gu, S., Baik, S., Hong, S., Moon, G., Son, S., Lee, K.M., Wang, X., Chan, K.C.K., Yu, K., Dong, C., Loy, C.C., Fan, Y., Yu, J., Liu, D., Huang, T.S., Liu, X., Li, C., He, D., DIng, Y., Wen, S., Porikli, F., Kalarot, R., Haris, M., Shakhnarovich, G., Ukita, N., Yi, P., Wang, Z., Jiang, K., Jiang, J., Ma, J., Dong, H., Zhang, X., Hu, Z., Kim, K., Kang, D.U., Chun, S.Y., Purohit, K., Rajagopalan, A.N., Tian, Y., Zhang, Y., Fu, Y., Xu, C., Yılmaz, M.A., Korkmaz, C., Sharma, M., Makwana, M., Badhwar, A., Singh, A.P., Upadhyay, A., Mukhopadhyay, R., Shukla, A., Khanna, D., Mandal, A.S., Chaudhury, S., Miao, S., Zhu, Y., Huo, X., College of Engineering, and Department of Electrical and Electronics Engineering

Subjects
Computer science, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, Image resolution, Image restoration, Video signal processing, Track (rail transport), Superresolution, Optical resolving power, Image super, 0202 electrical engineering, electronic engineering, information engineering, Bicubic interpolation, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, Focus (optics), business
Abstract

This paper reviews the first NTIRE challenge on video super-resolution (restoration of rich details in low-resolution video frames) with focus on proposed solutions and results. A new REalistic and Diverse Scenes dataset (REDS) was employed. The challenge was divided into 2 tracks. Track 1 employed standard bicubic downscaling setup while Track 2 had realistic dynamic motion blurs. Each competition had 124 and 104 registered participants. There were total 14 teams in the final testing phase. They gauge the state-of-the-art in video super-resolution., NA

Published
2019
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