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