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 • 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.