11 citations · 27 across the 9 of their papers we have counts for
6 papers · 1 filter
RFD-ECNet: Extreme Underwater Image Compression with Reference to Feature Dictionar
Mengyao Li, Liquan Shen, Peng Ye +2
Thriving underwater applications demand efficient extreme compression technology to realize the transmission of underwater images (UWIs) in very narrow underwater bandwidth. Howeve…
UIERL: Internal-External Representation Learning Network for Underwater Image Enhancement
Zhengyong Wang, Liquan Shen, Yihan Yu +1
Underwater image enhancement (UIE) is a meaningful but challenging task, and many learning-based UIE methods have been proposed in recent years. Although much progress has been mad…
Multi-Modality Deep Network for JPEG Artifacts Reduction
Xuhao Jiang, Weimin Tan, Qing Lin +3
In recent years, many convolutional neural network-based models are designed for JPEG artifacts reduction, and have achieved notable progress. However, few methods are suitable for…
Domain Adaptation for Underwater Image Enhancement
Zhengyong Wang, Liquan Shen, Mei Yu +3
Recently, learning-based algorithms have shown impressive performance in underwater image enhancement. Most of them resort to training on synthetic data and achieve outstanding per…
Single Underwater Image Enhancement Using an Analysis-Synthesis Network
Zhengyong Wang, Liquan Shen, Mei Yu +2
Most deep models for underwater image enhancement resort to training on synthetic datasets based on underwater image formation models. Although promising performances have been ach…
Deep Optimization model for Screen Content Image Quality Assessment using Neural Networks
Xuhao Jiang, Liquan Shen, Guorui Feng +2
In this paper, we propose a novel quadratic optimized model based on the deep convolutional neural network (QODCNN) for full-reference and no-reference screen content image (SCI) q…