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Chen Change Loy - IEEE Xplore Author Profile

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Author details

Chen Change Loy

Also published under: Chen-Change Loy

Publications

160

Citations

26,780

Publications by Year

20072025

Co-Authors:

Swaroop A.Abhinav AgarwallaEirikur AgustssonQiming AiNikhil Akalwadi

Show All Co-Authors (605)

Chen Change Loy

Also published under: Chen-Change Loy

Affiliation

S-Lab, Nanyang Technological University (NTU), Singapore

Publication Topics

Latent Space,
Generative Adversarial Networks,
Latent Code,
Self-supervised Learning,
Training Data,
Face Images,
Paired Data,
Attention Mechanism,
Convolutional Layers,
Fréchet Inception Distance,
Human Faces,
Identity Preservation

Biography

Chen Change Loy received the PhD degree in computer science from the Queen Mary University of London in 2010. He is currently a research assistant professor in the Department of Information Engineering, Chinese University of Hong Kong. Previously he was a postdoctoral researcher at Vision Semantics Ltd. His research interests include computer vision and pattern recognition, with focus on face analysis, deep learning, and visual surveillance. He is a member of the IEEE.(Based on document published on 7 July 2016).

Publications

160

Citations

26,780

Publications by Year

20072025

Co-Authors:

Swaroop A.
Abhinav Agarwalla
Eirikur Agustsson
Qiming Ai
Nikhil Akalwadi

Show All Co-Authors (605)

Author's Published Works

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Showing 1-2 of 2 results

Conferences (2)

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Lin Zha(2)
Jiande Jiang(2)
Jong Chul Ye(1)
Shengchen Zhu(1)
Zhipeng Luo(1)
Qingdao Hi-image Technologies Co.,Ltd (Hisense Visual Technology Co.,Ltd.)(1)
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(1)
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(1)
IEEE(2)
New Orleans, LA, USA(1)
Seattle, WA, USA(1)
Low-resolution Images(2)
Residual Block(2)
Single Image Super-resolution(2)
Super-resolution(2)
Adam Optimizer(1)

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Results

Asymmetric Information Distillation Network for Lightweight Super Resolution

Zhikai Zong;Lin Zha;Jiande Jiang;Xiaoxiao Liu

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2022 | Conference Paper |

Cited by: Papers (5)

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The purpose of this paper is to design a lightweight network to achieve image super resolution performance equivalent to SRResNet. We design an asymmetric information distillation block (AIDB) with distillation information multiplexing and asymmetric information extraction capabilities to better achieve this goal. Distillation information multiplexing refers to the repeated processing of distilled...Show More

Asymmetric Information Distillation Network for Lightweight Super Resolution

Zhikai Zong;Lin Zha;Jiande Jiang;Xiaoxiao Liu

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2022 | Conference Paper |

NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results

Kai Zhang;Shuhang Gu;Radu Timofte;Taizhang Shang;Qiuju Dai;Shengchen Zhu;Tong Yang;Yandong Guo;Younghyun Jo;Sejong Yang;Seon Joo Kim;Lin Zha;Jiande Jiang;Xinbo Gao;Wen Lu;Jing Liu;Kwangjin Yoon;Taegyun Jeon;Kazutoshi Akita;Takeru Ooba;Norimichi Ukita;Zhipeng Luo;Yuehan Yao;Zhenyu Xu;Dongliang He;Wenhao Wu;Yukang Ding;Chao Li;Fu Li;Shilei Wen;Jianwei Li;Fuzhi Yang;Huan Yang;Jianlong Fu;Byung-Hoon Kim;JaeHyun Baek;Jong Chul Ye;Yuchen Fan;Thomas S. Huang;Junyeop Lee;Bokyeung Lee;Jungki Min;Gwantae Kim;Kanghyu Lee;Jaihyun Park;Mykola Mykhailych;Haoyu Zhong;Yukai Shi;Xiaojun Yang;Zhijing Yang;Liang Lin;Tongtong Zhao;Jinjia Peng;Huibing Wang;Zhi Jin;Jiahao Wu;Yifu Chen;Chenming Shang;Huanrong Zhang;Jeongki Min;P.S. Hrishikesh;Densen Puthussery;C.V. Jiji

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2020 | Conference Paper |

Cited by: Papers (32)

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This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor ×16 based on a set of prior examples of low and corresponding high resolution images. The goal is to obtain a network design capable to produce high resolution results with the best percep...Show More

NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results

Kai Zhang;Shuhang Gu;Radu Timofte;Taizhang Shang;Qiuju Dai;Shengchen Zhu;Tong Yang;Yandong Guo;Younghyun Jo;Sejong Yang;Seon Joo Kim;Lin Zha;Jiande Jiang;Xinbo Gao;Wen Lu;Jing Liu;Kwangjin Yoon;Taegyun Jeon;Kazutoshi Akita;Takeru Ooba;Norimichi Ukita;Zhipeng Luo;Yuehan Yao;Zhenyu Xu;Dongliang He;Wenhao Wu;Yukang Ding;Chao Li;Fu Li;Shilei Wen;Jianwei Li;Fuzhi Yang;Huan Yang;Jianlong Fu;Byung-Hoon Kim;JaeHyun Baek;Jong Chul Ye;Yuchen Fan;Thomas S. Huang;Junyeop Lee;Bokyeung Lee;Jungki Min;Gwantae Kim;Kanghyu Lee;Jaihyun Park;Mykola Mykhailych;Haoyu Zhong;Yukai Shi;Xiaojun Yang;Zhijing Yang;Liang Lin;Tongtong Zhao;Jinjia Peng;Huibing Wang;Zhi Jin;Jiahao Wu;Yifu Chen;Chenming Shang;Huanrong Zhang;Jeongki Min;P.S. Hrishikesh;Densen Puthussery;C.V. Jiji

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2020 | Conference Paper |

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