no code implementations • 22 Apr 2024 • Xiaoning Liu, Zongwei Wu, Ao Li, Florin-Alexandru Vasluianu, Yulun Zhang, Shuhang Gu, Le Zhang, Ce Zhu, Radu Timofte, Zhi Jin, Hongjun Wu, Chenxi Wang, Haitao Ling, Yuanhao Cai, Hao Bian, Yuxin Zheng, Jing Lin, Alan Yuille, Ben Shao, Jin Guo, Tianli Liu, Mohao Wu, Yixu Feng, Shuo Hou, Haotian Lin, Yu Zhu, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang, Qingsen Yan, Wenbin Zou, Weipeng Yang, Yunxiang Li, Qiaomu Wei, Tian Ye, Sixiang Chen, Zhao Zhang, Suiyi Zhao, Bo wang, Yan Luo, Zhichao Zuo, Mingshen Wang, Junhu Wang, Yanyan Wei, Xiaopeng Sun, Yu Gao, Jiancheng Huang, Hongming Chen, Xiang Chen, Hui Tang, Yuanbin Chen, Yuanbo Zhou, Xinwei Dai, Xintao Qiu, Wei Deng, Qinquan Gao, Tong Tong, Mingjia Li, Jin Hu, Xinyu He, Xiaojie Guo, sabarinathan, K Uma, A Sasithradevi, B Sathya Bama, S. Mohamed Mansoor Roomi, V. Srivatsav, Jinjuan Wang, Long Sun, Qiuying Chen, Jiahong Shao, Yizhi Zhang, Marcos V. Conde, Daniel Feijoo, Juan C. Benito, Alvaro García, Jaeho Lee, Seongwan Kim, Sharif S M A, Nodirkhuja Khujaev, Roman Tsoy, Ali Murtaza, Uswah Khairuddin, Ahmad 'Athif Mohd Faudzi, Sampada Malagi, Amogh Joshi, Nikhil Akalwadi, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudenagudi, Wenyi Lian, Wenjing Lian, Jagadeesh Kalyanshetti, Vijayalaxmi Ashok Aralikatti, Palani Yashaswini, Nitish Upasi, Dikshit Hegde, Ujwala Patil, Sujata C, Xingzhuo Yan, Wei Hao, Minghan Fu, Pooja Choksy, Anjali Sarvaiya, Kishor Upla, Kiran Raja, Hailong Yan, Yunkai Zhang, Baiang Li, Jingyi Zhang, Huan Zheng
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.
1 code implementation • 14 Dec 2023 • Wenbin Zou, Hongxia Gao, Tian Ye, Liang Chen, Weipeng Yang, Shasha Huang, Hongsheng Chen, Sixiang Chen
In this paper, we propose Clearer Night Image Restoration with Vector-Quantized Codebook (VQCNIR) to achieve remarkable and consistent restoration outcomes on real-world and synthetic benchmarks.
1 code implementation • ICCV 2023 • Sixiang Chen, Tian Ye, Jinbin Bai, ErKang Chen, Jun Shi, Lei Zhu
In the real world, image degradations caused by rain often exhibit a combination of rain streaks and raindrops, thereby increasing the challenges of recovering the underlying clean image.
1 code implementation • 16 May 2023 • Yun Liu, Zhongsheng Yan, Sixiang Chen, Tian Ye, Wenqi Ren, ErKang Chen
Extensive experiments on several synthetic and real-world datasets demonstrate the superiority of our NightHazeFormer over state-of-the-art nighttime haze removal methods in terms of both visually and quantitatively.
1 code implementation • 15 May 2023 • Jingxia Jiang, Tian Ye, Jinbin Bai, Sixiang Chen, Wenhao Chai, Shi Jun, Yun Liu, ErKang Chen
In this work, we propose the Five A$^{+}$ Network (FA$^{+}$Net), a highly efficient and lightweight real-time underwater image enhancement network with only $\sim$ 9k parameters and $\sim$ 0. 01s processing time.
no code implementations • 13 Mar 2023 • Sixiang Chen, Tian Ye, Jun Shi, Yun Liu, Jingxia Jiang, ErKang Chen, Peng Chen
Varicolored haze caused by chromatic casts poses haze removal and depth estimation challenges.
no code implementations • 23 Feb 2023 • Jingxia Jiang, Jinbin Bai, Yun Liu, Junjie Yin, Sixiang Chen, Tian Ye, ErKang Chen
Underwater images typically experience mixed degradations of brightness and structure caused by the absorption and scattering of light by suspended particles.
no code implementations • ICCV 2023 • Tian Ye, Sixiang Chen, Jinbin Bai, Jun Shi, Chenghao Xue, Jingxia Jiang, Junjie Yin, ErKang Chen, Yun Liu
Inspired by recent advancements in codebook and vector quantization (VQ) techniques, we present a novel Adverse Weather Removal network with Codebook Priors (AWRCP) to address the problem of unified adverse weather removal.
no code implementations • 3 Oct 2022 • Sixiang Chen, Tian Ye, Yun Liu, ErKang Chen
Recently, image restoration transformers have achieved comparable performance with previous state-of-the-art CNNs.
1 code implementation • 20 Aug 2022 • Sixiang Chen, Tian Ye, Yun Liu, ErKang Chen
Due to various and complicated snow degradations, single image desnowing is a challenging image restoration task.
no code implementations • 12 Jul 2022 • Sixiang Chen, Tian Ye, Yun Liu, Taodong Liao, Jingxia Jiang, ErKang Chen, Peng Chen
Snow removal causes challenges due to its characteristic of complex degradations.
no code implementations • 12 Jul 2022 • Tian Ye, Sixiang Chen, Yun Liu, Yi Ye, ErKang Chen
In winter scenes, the degradation of images taken under snow can be pretty complex, where the spatial distribution of snowy degradation is varied from image to image.
no code implementations • 19 Apr 2022 • Tian Ye, Sixiang Chen, Yun Liu, ErKang Chen, Yuche Li
A single expert network efficiently addresses specific degradation in nasty winter scenes relying on the compact architecture and three novel components.
1 code implementation • 21 Mar 2022 • Tian Ye, Sixiang Chen, Yun Liu, Yi Ye, ErKang Chen, Yuche Li
To this end, we propose a neural rendering method for underwater imaging, dubbed UWNR (Underwater Neural Rendering).
no code implementations • 17 Mar 2022 • Tian Ye, Yun Liu, Yunchen Zhang, Sixiang Chen, ErKang Chen
Specifically, we first devise two siamese networks: a teacher network in the synthetic domain and a student network in the real domain, and then optimize them in a mutual learning manner by leveraging EMA and joint loss.