D
Ding Liu
Researcher at University of Illinois at Urbana–Champaign
Publications - 65
Citations - 8423
Ding Liu is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Deep learning & Image restoration. The author has an hindex of 27, co-authored 65 publications receiving 5745 citations.
Papers
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Proceedings ArticleDOI
Understanding Convolution for Semantic Segmentation
TL;DR: DUC is designed to generate pixel-level prediction, which is able to capture and decode more detailed information that is generally missing in bilinear upsampling, and a hybrid dilated convolution (HDC) framework in the encoding phase is proposed.
Proceedings ArticleDOI
NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results
Radu Timofte,Eirikur Agustsson,Luc Van Gool,Ming-Hsuan Yang,Lei Zhang,Bee Oh Lim,Sanghyun Son,Heewon Kim,Seungjun Nah,Kyoung Mu Lee,Xintao Wang,Yapeng Tian,Ke Yu,Yulun Zhang,Shixiang Wu,Chao Dong,Liang Lin,Yu Qiao,Chen Change Loy,Woong Bae,Jaejun Yoo,Yoseob Han,Jong Chul Ye,Jae-Seok Choi,Munchurl Kim,Yuchen Fan,Jiahui Yu,Wei Han,Ding Liu,Haichao Yu,Zhangyang Wang,Honghui Shi,Xinchao Wang,Thomas S. Huang,Yunjin Chen,Kai Zhang,Wangmeng Zuo,Zhimin Tang,Linkai Luo,Shaohui Li,Min Fu,Lei Cao,Wen Heng,Giang Bui,Truc Le,Ye Duan,Dacheng Tao,Ruxin Wang,Xu Lin,Jianxin Pang,Xu Jinchang,Yu Zhao,Xiangyu Xu,Jinshan Pan,Deqing Sun,Yujin Zhang,Xibin Song,Yuchao Dai,Xueying Qin,Xuan-Phung Huynh,Tiantong Guo,Hojjat Seyed Mousavi,Tiep H. Vu,Vishal Monga,Cristóvão Cruz,Karen Egiazarian,Vladimir Katkovnik,Rakesh Mehta,Arnav Kumar Jain,Abhinav Agarwalla,Ch V. Sai Praveen,Ruofan Zhou,Hongdiao Wen,Che Zhu,Zhiqiang Xia,Zhengtao Wang,Qi Guo +76 more
TL;DR: This paper reviews the first challenge on single image super-resolution (restoration of rich details in an low resolution image) with focus on proposed solutions and results and gauges the state-of-the-art in single imagesuper-resolution.
Proceedings ArticleDOI
Deep Networks for Image Super-Resolution with Sparse Prior
TL;DR: In this paper, the authors argue that domain expertise represented by the conventional sparse coding model is still valuable, and it can be combined with the key ingredients of deep learning to achieve further improved results.
Posted Content
Understanding Convolution for Semantic Segmentation
TL;DR: Zhang et al. as mentioned in this paper design dense upsampling convolution (DUC) to generate pixel-level prediction, which is able to capture and decode more detailed information that is generally missing in bilinear upampling.
Journal ArticleDOI
EnlightenGAN: Deep Light Enhancement Without Paired Supervision
Yifan Jiang,Xinyu Gong,Ding Liu,Yu Cheng,Chen Fang,Xiaohui Shen,Jianchao Yang,Pan Zhou,Zhangyang Wang +8 more
TL;DR: EnlightenGAN as mentioned in this paper proposes a highly effective unsupervised generative adversarial network that can be trained without low/normal-light image pairs, yet proves to generalize very well on various real-world test images.