168 citations · 513 across the 28 of their papers we have counts for
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Deep Multi-Scale Features Learning for Distorted Image Quality Assessment
Wei Zhou, Zhibo Chen
Image quality assessment (IQA) aims to estimate human perception based image visual quality. Although existing deep neural networks (DNNs) have shown significant effectiveness for…
Deep Local and Global Spatiotemporal Feature Aggregation for Blind Video Quality Assessment
Wei Zhou, Zhibo Chen
In recent years, deep learning has achieved promising success for multimedia quality assessment, especially for image quality assessment (IQA). However, since there exist more comp…
LIRA: Lifelong Image Restoration from Unknown Blended Distortions
Jianzhao Liu, Jianxin Lin, Xin Li +3
Most existing image restoration networks are designed in a disposable way and catastrophically forget previously learned distortions when trained on a new distortion removal task.…
Learning Disentangled Feature Representation for Hybrid-distorted Image Restoration
Xin Li, Xin Jin, Jianxin Lin +5
Hybrid-distorted image restoration (HD-IR) is dedicated to restore real distorted image that is degraded by multiple distortions. Existing HD-IR approaches usually ignore the inher…
Blind Quality Assessment for Image Superresolution Using Deep Two-Stream Convolutional Networks
Wei Zhou, Qiuping Jiang, Yuwang Wang +2
Numerous image superresolution (SR) algorithms have been proposed for reconstructing high-resolution (HR) images from input images with lower spatial resolutions. However, effectiv…
Blind Omnidirectional Image Quality Assessment with Viewport Oriented Graph Convolutional Networks
Jiahua Xu, Wei Zhou, Zhibo Chen
Quality assessment of omnidirectional images has become increasingly urgent due to the rapid growth of virtual reality applications. Different from traditional 2D images and videos…