58 citations · 82 across the 15 of their papers we have counts for
9 papers · 1 filter
Adaptive Hypergraph Convolutional Network for No-Reference 360-degree Image Quality Assessment
Jun Fu, Chen Hou, Wei Zhou +2
In no-reference 360-degree image quality assessment (NR 360IQA), graph convolutional networks (GCNs), which model interactions between viewports through graphs, have achieved impre…
Image Super-Resolution Quality Assessment: Structural Fidelity Versus Statistical Naturalness
Wei Zhou, Zhou Wang, Zhibo Chen
Single image super-resolution (SISR) algorithms reconstruct high-resolution (HR) images with their low-resolution (LR) counterparts. It is desirable to develop image quality assess…
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.…
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…