9 citations · 9 across the 1 of their papers we have counts for
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A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning
Xiaofeng Cong, Yu Zhao, Jie Gui +2
Underwater image enhancement (UIE) presents a significant challenge within computer vision research. Despite the development of numerous UIE algorithms, a thorough and systematic r…
The Devil is in the Darkness: Diffusion-Based Nighttime Dehazing Anchored in Brightness Perception
Xiaofeng Cong, Yu-Xin Zhang, Haoran Wei +5
While nighttime image dehazing has been extensively studied, converting nighttime hazy images to daytime-equivalent brightness remains largely unaddressed. Existing methods face tw…
Deep Learning-Based Point Cloud Registration: A Comprehensive Survey and Taxonomy
Yu-Xin Zhang, Jie Gui, Baosheng Yu +4
Point cloud registration involves determining a rigid transformation to align a source point cloud with a target point cloud. This alignment is fundamental in applications such as…
Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and Interpolation
Xiaofeng Cong, Jing Zhang, Yeying Jin +5
Underwater images often suffer from quality degradation due to absorption and scattering effects. Most existing underwater image enhancement algorithms produce a single, fixed-colo…
A Semi-supervised Nighttime Dehazing Baseline with Spatial-Frequency Aware and Realistic Brightness Constraint
Xiaofeng Cong, Jie Gui, Jing Zhang +2
Existing research based on deep learning has extensively explored the problem of daytime image dehazing. However, few studies have considered the characteristics of nighttime hazy…