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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 26–46 of 46 papers

TitleStatusHype
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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