1 code implementation • 12 Jul 2022 • Haolin Wang, Jiawei Zhang, Ming Liu, Xiaohe Wu, WangMeng Zuo
In particular, the style encoder predicts the target style representation of an input image, which serves as the conditional information in the RetouchNet for retouching, while the TSFlow maps the style representation vector into a Gaussian distribution in the forward pass.
no code implementations • 24 Dec 2021 • Jize Zhang, Haolin Wang, Xiaohe Wu, WangMeng Zuo
Existing unpaired low-light image enhancement approaches prefer to employ the two-way GAN framework, in which two CNN generators are deployed for enhancement and degradation separately.
1 code implementation • ICCV 2021 • Zhilu Zhang, Haolin Wang, Ming Liu, Ruohao Wang, Jiawei Zhang, WangMeng Zuo
To diminish the effect of color inconsistency in image alignment, we introduce to use a global color mapping (GCM) module to generate an initial sRGB image given the input raw image, which can keep the spatial location of the pixels unchanged, and the target sRGB image is utilized to guide GCM for converting the color towards it.
1 code implementation • 10 Nov 2020 • 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
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results.
1 code implementation • ECCV 2020 • Yuxiang Wei, Ming Liu, Haolin Wang, Ruifeng Zhu, Guosheng Hu, WangMeng Zuo
Despite recent advances in deep learning-based face frontalization methods, photo-realistic and illumination preserving frontal face synthesis is still challenging due to large pose and illumination discrepancy during training.