1 code implementation • 15 Jun 2023 • Runmin Cong, Wenyu Yang, Wei zhang, Chongyi Li, Chun-Le Guo, Qingming Huang, Sam Kwong
Among existing UIE methods, Generative Adversarial Networks (GANs) based methods perform well in visual aesthetics, while the physical model-based methods have better scene adaptability.
no code implementations • 6 May 2023 • Xin Lin, Jingtong Yue, Sixian Ding, Chao Ren, Chun-Le Guo, Chongyi Li
P-Net can learn degradation feature vectors on the dark and light areas separately, using contrastive learning to guide the image restoration process.
5 code implementations • CVPR 2023 • Zhen Li, Zuo-Liang Zhu, Ling-Hao Han, Qibin Hou, Chun-Le Guo, Ming-Ming Cheng
It is based on two essential designs.
2 code implementations • CVPR 2023 • Rui-Qi Wu, Zheng-Peng Duan, Chun-Le Guo, Zhi Chai, Chong-Yi Li
(2) We propose a Real Image Dehazing network via high-quality Codebook Priors (RIDCP).
1 code implementation • ICCV 2023 • Yupeng Zhou, Zhen Li, Chun-Le Guo, Song Bai, Ming-Ming Cheng, Qibin Hou
Previous works have shown that increasing the window size for Transformer-based image super-resolution models (e. g., SwinIR) can significantly improve the model performance but the computation overhead is also considerable.
1 code implementation • 23 Feb 2023 • Chongyi Li, Chun-Le Guo, Man Zhou, Zhexin Liang, Shangchen Zhou, Ruicheng Feng, Chen Change Loy
Our approach is motivated by a few unique characteristics in the Fourier domain: 1) most luminance information concentrates on amplitudes while noise is closely related to phases, and 2) a high-resolution image and its low-resolution version share similar amplitude patterns. Through embedding Fourier into our network, the amplitude and phase of a low-light image are separately processed to avoid amplifying noise when enhancing luminance.
2 code implementations • CVPR 2023 • Xin Jin, Ling-Hao Han, Zhen Li, Chun-Le Guo, Zhi Chai, Chongyi Li
The exclusive properties of RAW data have shown great potential for low-light image enhancement.
1 code implementation • 21 Jul 2022 • Zuo-Liang Zhu, Zhen Li, Rui-Xun Zhang, Chun-Le Guo, Ming-Ming Cheng
Lighting is a determining factor in photography that affects the style, expression of emotion, and even quality of images.
no code implementations • 10 Apr 2022 • Ziyue Zhu, Zhao Zhang, Zheng Lin, Ruiqi Wu, Zhi Chai, Chun-Le Guo
To achieve visual consistency in composite images, recent image harmonization methods typically summarize the appearance pattern of global background and apply it to the global foreground without location discrepancy.
2 code implementations • CVPR 2022 • Zhen Li, Cheng-Ze Lu, Jianhua Qin, Chun-Le Guo, Ming-Ming Cheng
Optical flow, which captures motion information across frames, is exploited in recent video inpainting methods through propagating pixels along its trajectories.
Ranked #2 on Seeing Beyond the Visible on KITTI360-EX
2 code implementations • CVPR 2022 • Zheng Lin, Zheng-Peng Duan, Zhao Zhang, Chun-Le Guo, Ming-Ming Cheng
However, the global view makes the model lose focus from later clicks, and is not in line with user intentions.
Ranked #5 on Interactive Segmentation on SBD
2 code implementations • CVPR 2022 • Chun-Le Guo, Qixin Yan, Saeed Anwar, Runmin Cong, Wenqi Ren, Chongyi Li
Though Transformer has occupied various computer vision tasks, directly leveraging Transformer for image dehazing is challenging: 1) it tends to result in ambiguous and coarse details that are undesired for image reconstruction; 2) previous position embedding of Transformer is provided in logic or spatial position order that neglects the variational haze densities, which results in the sub-optimal dehazing performance.