5 citations · 10 across the 6 of their papers we have counts for
6 papers
Underwater Image Enhancement with Cascaded Contrastive Learning
Yi Liu, Qiuping Jiang, Xinyi Wang +2
Underwater image enhancement (UIE) is a highly challenging task due to the complexity of underwater environment and the diversity of underwater image degradation. Due to the applic…
IA2U: A Transfer Plugin with Multi-Prior for In-Air Model to Underwater
Jingchun Zhou, Qilin Gai, Kin-man Lam +1
In underwater environments, variations in suspended particle concentration and turbidity cause severe image degradation, posing significant challenges to image enhancement (IE) and…
WaterHE-NeRF: Water-ray Tracing Neural Radiance Fields for Underwater Scene Reconstruction
Jingchun Zhou, Tianyu Liang, Dehuan Zhang +1
Neural Radiance Field (NeRF) technology demonstrates immense potential in novel viewpoint synthesis tasks, due to its physics-based volumetric rendering process, which is particula…
DGNet: Dynamic Gradient-Guided Network for Water-Related Optics Image Enhancement
Jingchun Zhou, Zongxin He, Qiuping Jiang +3
Underwater image enhancement (UIE) is a challenging task due to the complex degradation caused by underwater environments. To solve this issue, previous methods often idealize the…
Synergistic Multiscale Detail Refinement via Intrinsic Supervision for Underwater Image Enhancement
Dehuan Zhang, Jingchun Zhou, ChunLe Guo +2
Visually restoring underwater scenes primarily involves mitigating interference from underwater media. Existing methods ignore the inherent scale-related characteristics in underwa…
AMSP-UOD: When Vortex Convolution and Stochastic Perturbation Meet Underwater Object Detection
Jingchun Zhou, Zongxin He, Kin-Man Lam +4
In this paper, we present a novel Amplitude-Modulated Stochastic Perturbation and Vortex Convolutional Network, AMSP-UOD, designed for underwater object detection. AMSP-UOD specifi…