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Blind Image Quality Assessment

To avoid duplication and fragmentation, use the No-Reference Image Quality Assessment (NR-IQA) task.

Papers

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Showing 1–46 of 46 papers

TitleStatusHype
Taylor expansion-based Kolmogorov-Arnold network for blind image quality assessmentCode1
Bridging the Synthetic-to-Authentic Gap: Distortion-Guided Unsupervised Domain Adaptation for Blind Image Quality AssessmentCode0
Attention Down-Sampling Transformer, Relative Ranking and Self-Consistency for Blind Image Quality AssessmentCode0
No-Reference Image Quality Assessment with Global-Local Progressive Integration and Semantic-Aligned Quality TransferCode0
FreqAlign: Excavating Perception-oriented Transferability for Blind Image Quality Assessment from A Frequency PerspectiveCode0
UHD-IQA Benchmark Database: Pushing the Boundaries of Blind Photo Quality AssessmentCode0
DDR: Exploiting Deep Degradation Response as Flexible Image DescriptorCode0
Blind Image Quality Assessment: A Brief Survey—0
Blind Image Quality Assessment for MRI with A Deep Three-dimensional content-adaptive Hyper-Network—0
Blind Image Quality Assessment Using Multi-Stream Architecture with Spatial and Channel Attention—0
Blind Image Quality Assessment using Semi-supervised Rectifier Networks—0
Blind Multimodal Quality Assessment of Low-light Images—0
Blind Predicting Similar Quality Map for Image Quality Assessment—0
Computational Analysis of Degradation Modeling in Blind Panoramic Image Quality Assessment—0
Coupled Learning for Facial Deblur—0
Cross-Dataset-Robust Method for Blind Real-World Image Quality Assessment—0
Deep Decomposition and Bilinear Pooling Network for Blind Night-Time Image Quality Evaluation—0
Deep Ensembling for Perceptual Image Quality Assessment—0
Deep Neural Network for Blind Visual Quality Assessment of 4K Content—0
Deep Neural Networks for Blind Image Quality Assessment: Addressing the Data Challenge—0
Deep Shape-Texture Statistics for Completely Blind Image Quality Evaluation—0
dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs—0
Distilling Spatially-Heterogeneous Distortion Perception for Blind Image Quality Assessment—0
ExIQA: Explainable Image Quality Assessment Using Distortion Attributes—0
Feature Denoising Diffusion Model for Blind Image Quality Assessment—0
GreenBIQA: A Lightweight Blind Image Quality Assessment Method—0
GSBIQA: Green Saliency-guided Blind Image Quality Assessment Method—0
Learning to Rank for Blind Image Quality Assessment—0
Learning without Human Scores for Blind Image Quality Assessment—0
Lightweight High-Performance Blind Image Quality Assessment—0
Massive Online Crowdsourced Study of Subjective and Objective Picture Quality—0
On the Use of Deep Learning for Blind Image Quality Assessment—0
Quality-aware Pre-trained Models for Blind Image Quality Assessment—0
Scale Contrastive Learning with Selective Attentions for Blind Image Quality Assessment—0
Source-free Unsupervised Domain Adaptation for Blind Image Quality Assessment—0
Active Fine-Tuning from gMAD Examples Improves Blind Image Quality Assessment—0
Stochastic BIQA: Median Randomized Smoothing for Certified Blind Image Quality Assessment—0
Subjective and Objective De-raining Quality Assessment Towards Authentic Rain Image—0
Troubleshooting Blind Image Quality Models in the Wild—0
Spatial Moment Pooling Improves Neural Image Assessment—0
Adaptive Mixed-Scale Feature Fusion Network for Blind AI-Generated Image Quality Assessment—0
A Lightweight Parallel Framework for Blind Image Quality Assessment—0
A proposal project for a blind image quality assessment by learning distortions from the full reference image quality assessments—0
Beyond Human Opinion Scores: Blind Image Quality Assessment based on Synthetic Scores—0
BIQ2021: A Large-Scale Blind Image Quality Assessment Database—0
Blind CT Image Quality Assessment Using DDPM-derived Content and Transformer-based Evaluator—0
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