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NR-IQA

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

Papers

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Showing 1–50 of 50 papers

TitleStatusHype
VisualQuality-R1: Reasoning-Induced Image Quality Assessment via Reinforcement Learning to RankCode2
Exploring Semantic Feature Discrimination for Perceptual Image Super-Resolution and Opinion-Unaware No-Reference Image Quality AssessmentCode1
AIM 2024 Challenge on UHD Blind Photo Quality AssessmentCode1
Diffusion Model Based Visual Compensation Guidance and Visual Difference Analysis for No-Reference Image Quality AssessmentCode1
DGIQA: Depth-guided Feature Attention and Refinement for Generalizable Image Quality AssessmentCode0
Semantically-Aware Game Image Quality Assessment—0
Cross-Domain Underwater Image Enhancement Guided by No-Reference Image Quality Assessment: A Transfer Learning Approach—0
IQPFR: An Image Quality Prior for Blind Face Restoration and Beyond—0
Augmenting Perceptual Super-Resolution via Image Quality Predictors—0
Backdoor Attacks against No-Reference Image Quality Assessment Models via a Scalable TriggerCode0
Light Field Image Quality Assessment With Auxiliary Learning Based on Depthwise and Anglewise Separable Convolutions—0
Stochastic BIQA: Median Randomized Smoothing for Certified Blind Image Quality Assessment—0
Visual question answering based evaluation metrics for text-to-image generation—0
Multi-task Feature Enhancement Network for No-Reference Image Quality Assessment—0
Attention Down-Sampling Transformer, Relative Ranking and Self-Consistency for Blind Image Quality AssessmentCode0
MSLIQA: Enhancing Learning Representations for Image Quality Assessment through Multi-Scale Learning—0
A Deep-Learning-Based Label-free No-Reference Image Quality Assessment Metric: Application in Sodium MRI Denoising—0
Local Manifold Learning for No-Reference Image Quality Assessment—0
UHD-IQA Benchmark Database: Pushing the Boundaries of Blind Photo Quality AssessmentCode0
GenzIQA: Generalized Image Quality Assessment using Prompt-Guided Latent Diffusion Models—0
Rank-based No-reference Quality Assessment for Face Swapping—0
ATTIQA: Generalizable Image Quality Feature Extractor using Attribute-aware Pretraining—0
Cross-IQA: Unsupervised Learning for Image Quality Assessment—0
Image Quality Assessment With Compressed Sampling—0
Beyond Score Changes: Adversarial Attack on No-Reference Image Quality Assessment from Two Perspectives—0
When No-Reference Image Quality Models Meet MAP Estimation in Diffusion Latents—0
Black-box Adversarial Attacks Against Image Quality Assessment Models—0
Exploring Vulnerabilities of No-Reference Image Quality Assessment Models: A Query-Based Black-Box Method—0
Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivity—0
Less is More: Learning Reference Knowledge Using No-Reference Image Quality Assessment—0
Interpretable Image Quality Assessment via CLIP with Multiple Antonym-Prompt Pairs—0
JNDMix: JND-Based Data Augmentation for No-reference Image Quality Assessment—0
StyleAM: Perception-Oriented Unsupervised Domain Adaption for Non-reference Image Quality Assessment—0
Subjective Quality Assessment for Images Generated by Computer Graphics—0
ER-IQA: Boosting Perceptual Quality Assessment Using External Reference Images—0
Perceptual Image Restoration with High-Quality Priori and Degradation Learning—0
Comprehensive evaluation of no-reference image quality assessment algorithms on authentic distortions—0
Multi-task deep CNN model for no-reference image quality assessment on smartphone camera photos—0
No-Reference Image Quality Assessment via Feature Fusion and Multi-Task Learning—0
Domain Fingerprints for No-reference Image Quality Assessment—0
Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data—0
Deep Optimization model for Screen Content Image Quality Assessment using Neural Networks—0
Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning—0
RAN4IQA: Restorative Adversarial Nets for No-Reference Image Quality Assessment—0
An Attention-Driven Approach of No-Reference Image Quality Assessment—0
MUG: A Parameterless No-Reference JPEG Quality Evaluator Robust to Block Size and Misalignment—0
Comparison-based Image Quality Assessment for Parameter Selection—0
SOM: Semantic Obviousness Metric for Image Quality Assessment—0
Quality Assessment for Comparing Image Enhancement Algorithms—0
Real-Time No-Reference Image Quality Assessment Based on Filter Learning—0
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