activity
20142024
most citedDeep Optimization model for Screen Content Image Quality Assessment using Neural Networks

11 citations · 27 across the 9 of their papers we have counts for

collaborators

9 papers

eess.IV2024★ 3 cited

Cuboid-Net: A Multi-Branch Convolutional Neural Network for Joint Space-Time Video Super Resolution

Congrui Fu, Hui Yuan, Hongji Xu +2

The demand for high-resolution videos has been consistently rising across various domains, propelled by continuous advancements in science, technology, and societal. Nonetheless, c…

cs.CV2023

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…

cs.CV2023

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…

cs.CV2023

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…

eess.IV2023★ 1 cited

Multi-Modality Deep Network for Extreme Learned Image Compression

Xuhao Jiang, Weimin Tan, Tian Tan +2

Image-based single-modality compression learning approaches have demonstrated exceptionally powerful encoding and decoding capabilities in the past few years , but suffer from blur…

cs.CV2021★ 2 cited

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…

cs.CV2021★ 9 cited

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…

cs.CV2019★ 11 cited

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…

cs.IT2014★ 1 cited

On the Power Allocation for Hybrid DF and CF Protocol with Auxiliary Parameter in Fading Relay Channels

Zhengchuan Chen, Pingyi Fan, Dapeng Wu +1

In fading channels, power allocation over channel state may bring a rate increment compared to the fixed constant power mode. Such a rate increment is referred to power allocation…