T
Tian Liang
Researcher at Chinese Academy of Sciences
Publications - 3
Citations - 89
Tian Liang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Color balance & Demosaicing. The author has an hindex of 3, co-authored 3 publications receiving 49 citations.
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AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov,Radu Timofte,Zhilu Zhang,Ming Liu,Haolin Wang,Wangmeng Zuo,Jiawei Zhang,Ruimao Zhang,Zhanglin Peng,Sijie Ren,Linhui Dai,Xiaohong Liu,Chengqi Li,Jun Chen,Yuichi Ito,Bhavya Vasudeva,Puneesh Deora,Umapada Pal,Zhenyu Guo,Yu Zhu,Tian Liang,Chenghua Li,Cong Leng,Zhihong Pan,Baopu Li,Byung-Hoon Kim,Joonyoung Song,Jong Chul Ye,JaeHyun Baek,Magauiya Zhussip,Yeskendir Koishekenov,Hwechul Cho Ye,Xin Liu,Xueying Hu,Jun Jiang,Jinwei Gu,Kai Li,Pengliang Tan,Bingxin Hou +38 more
TL;DR: This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results, defining the state-of-the-art for practical image signal processing pipeline modeling.
Book ChapterDOI
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov,Radu Timofte,Zhilu Zhang,Ming Liu,Haolin Wang,Wangmeng Zuo,Jiawei Zhang,Ruimao Zhang,Zhanglin Peng,Sijie Ren,Linhui Dai,Xiaohong Liu,Chengqi Li,Jun Chen,Yuichi Ito,Bhavya Vasudeva,Puneesh Deora,Umapada Pal,Zhenyu Guo,Yu Zhu,Tian Liang,Chenghua Li,Cong Leng,Zhihong Pan,Baopu Li,Byung-Hoon Kim,Joonyoung Song,Jong Chul Ye,JaeHyun Baek,Magauiya Zhussip,Yeskendir Koishekenov,Hwechul Cho Ye,Xin Liu,Xueying Hu,Jun Jiang,Jinwei Gu,Kai Li,Pengliang Tan,Bingxin Hou +38 more
TL;DR: The second AIM learned ISP challenge as mentioned in this paper focused on real-world RAW-to-RGB mapping problem, where the goal was to map the original low-quality RAW images captured by the Huawei P20 device to the same photos obtained with the Canon 5D DSLR camera.
Book ChapterDOI
EEDNet: Enhanced Encoder-Decoder Network for AutoISP
Yu Zhu,Zhenyu Guo,Tian Liang,Xiangyu He,Chenghua Li,Cong Leng,Bo Jiang,Yifan Zhang,Jian Cheng +8 more
TL;DR: EDNet as mentioned in this paper proposes a hypothesis of the receptive field that large receptive field is essential in high-level computer vision tasks, but not crucial in low-level pixel-to-pixel tasks.