168 citations · 513 across the 28 of their papers we have counts for
6 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…
LIQA: Lifelong Blind Image Quality Assessment
Jianzhao Liu, Wei Zhou, Jiahua Xu +3
Existing blind image quality assessment (BIQA) methods are mostly designed in a disposable way and cannot evolve with unseen distortions adaptively, which greatly limits the deploy…
Bayesian Graph Convolutional Network for Traffic Prediction
Jun Fu, Wei Zhou, Zhibo Chen
Recently, adaptive graph convolutional network based traffic prediction methods, learning a latent graph structure from traffic data via various attention-based mechanisms, have ac…
GraphIQA: Learning Distortion Graph Representations for Blind Image Quality Assessment
Simeng Sun, Tao Yu, Jiahua Xu +2
A good distortion representation is crucial for the success of deep blind image quality assessment (BIQA). However, most previous methods do not effectively model the relationship…
No-Reference Quality Assessment for 360-degree Images by Analysis of Multi-frequency Information and Local-global Naturalness
Wei Zhou, Jiahua Xu, Qiuping Jiang +1
360-degree/omnidirectional images (OIs) have achieved remarkable attentions due to the increasing applications of virtual reality (VR). Compared to conventional 2D images, OIs can…