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.
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 • 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.
no code implementations • 27 Apr 2023 • Haolin Wang, Yafei Ou, Wanxuan Fang, Prasoon Ambalathankandy, Naoto Goto, Gen Ota, Masayuki Ikebe, Tamotsu Kamishima
A new framework for monitoring joint space by quantifying JSN progression through image registration in radiographic images has been developed.
no code implementations • 5 Jun 2023 • Haolin Wang, Xuefeng Liu, Jianwei Niu, Shaojie Tang, Jiaxing Shen
Our further investigation shows that the decline is due to the continuous accumulation of dissimilarities among client models during the layer-by-layer back-propagation process, which we refer to as "divergence accumulation."
no code implementations • 29 Oct 2023 • Yuanze Li, Haolin Wang, Shihao Yuan, Ming Liu, Debin Zhao, Yiwen Guo, Chen Xu, Guangming Shi, WangMeng Zuo
Existing industrial anomaly detection (IAD) methods predict anomaly scores for both anomaly detection and localization.