SOTAVerified

No-Reference Image Quality Assessment

An Image Quality Assessment approach where no reference image information is available to the model. Sometimes referred to as Blind Image Quality Assessment (BIQA).

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–50 of 155 papers

TitleStatusHype
TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality AssessmentCode4
LAR-IQA: A Lightweight, Accurate, and Robust No-Reference Image Quality Assessment ModelCode2
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning PerspectiveCode2
MANIQA: Multi-dimension Attention Network for No-Reference Image Quality AssessmentCode2
Pairwise Comparisons Are All You NeedCode2
SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction TuningCode2
Exploring CLIP for Assessing the Look and Feel of ImagesCode2
Self2Self+: Single-Image Denoising with Self-Supervised Learning and Image Quality Assessment LossCode1
Re-IQA: Unsupervised Learning for Image Quality Assessment in the WildCode1
SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding RobustnessCode1
PromptIQA: Boosting the Performance and Generalization for No-Reference Image Quality Assessment via PromptsCode1
High Resolution Image Quality DatabaseCode1
REQA: Coarse-to-fine Assessment of Image Quality to Alleviate the Range EffectCode1
ARNIQA: Learning Distortion Manifold for Image Quality AssessmentCode1
Perceptual Quality Assessment of Smartphone PhotographyCode1
No-Reference Image Quality Assessment by Hallucinating Pristine FeaturesCode1
No-Reference Image Quality Assessment with Global Statistical FeaturesCode1
MetaIQA: Deep Meta-learning for No-Reference Image Quality AssessmentCode1
Analysis of Video Quality Datasets via Design of Minimalistic Video Quality ModelsCode1
No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-ConsistencyCode1
Norm-in-Norm Loss with Faster Convergence and Better Performance for Image Quality AssessmentCode1
Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-LoopCode1
Learning Generalizable Perceptual Representations for Data-Efficient No-Reference Image Quality AssessmentCode1
Point Cloud Quality Assessment: Dataset Construction and Learning-based No-Reference MetricCode1
Blind Image Quality Assessment via Transformer Predicted Error Map and Perceptual Quality TokenCode1
A CNN-Based Blind Denoising Method for Endoscopic ImagesCode1
Blindly Assess Image Quality in the Wild Guided by a Self-Adaptive Hyper NetworkCode1
MobileIQA: Exploiting Mobile-level Diverse Opinion Network For No-Reference Image Quality Assessment Using Knowledge DistillationCode1
AutoDIR: Automatic All-in-One Image Restoration with Latent DiffusionCode1
KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessmentCode1
Diffusion Model Based Visual Compensation Guidance and Visual Difference Analysis for No-Reference Image Quality AssessmentCode1
DP-IQA: Utilizing Diffusion Prior for Blind Image Quality Assessment in the WildCode1
AIM 2024 Challenge on UHD Blind Photo Quality AssessmentCode1
Conformer and Blind Noisy Students for Improved Image Quality AssessmentCode1
Content-Variant Reference Image Quality Assessment via Knowledge DistillationCode1
Continual Learning for Blind Image Quality AssessmentCode1
Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable BankCode1
Generalizable No-Reference Image Quality Assessment via Deep Meta-learningCode1
Learning to Blindly Assess Image Quality in the Laboratory and WildCode1
Exploring Semantic Feature Discrimination for Perceptual Image Super-Resolution and Opinion-Unaware No-Reference Image Quality AssessmentCode1
No-Reference Color Image Quality Assessment: From Entropy to Perceptual QualityCode1
Data-Efficient Image Quality Assessment with Attention-Panel DecoderCode1
Deep Feature Statistics Mapping for Generalized Screen Content Image Quality AssessmentCode1
Adaptive Image Quality Assessment via Teaching Large Multimodal Model to CompareCode1
Deep learning techniques for blind image super-resolution: A high-scale multi-domain perspective evaluationCode1
On the Effectiveness of Spectral Discriminators for Perceptual Quality ImprovementCode1
Blind Image Quality Assessment Based on Geometric Order LearningCode1
Image Quality Assessment using Contrastive LearningCode1
Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm RegularizationCode1
PKU-I2IQA: An Image-to-Image Quality Assessment Database for AI Generated ImagesCode1
Show:102550
← PrevPage 1 of 4Next →
All datasetsKADID-10kCSIQTID2013UHD-IQAKonIQ-10kLIVESPAQ

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RvTC (image-only)SRCC0.98—Unverified
2UNIQASRCC0.94—Unverified
3CONTRIQUESRCC0.93—Unverified
4ARNIQASRCC0.91—Unverified
5Re-IQASRCC0.87—Unverified
6TReSSRCC0.86—Unverified
7HyperIQASRCC0.85—Unverified
8DB-CNNSRCC0.85—Unverified
9BRISQUESRCC0.53—Unverified
#ModelMetricClaimedVerifiedStatus
1UNIQASRCC0.96—Unverified
2ARNIQASRCC0.96—Unverified
3Re-IQASRCC0.95—Unverified
4DB-CNNSRCC0.95—Unverified
5CONTRIQUESRCC0.94—Unverified
6HyperIQASRCC0.92—Unverified
7TReSSRCC0.92—Unverified
8BRISQUESRCC0.75—Unverified
#ModelMetricClaimedVerifiedStatus
1UNIQASRCC0.95—Unverified
2ARNIQASRCC0.88—Unverified
3TReSSRCC0.86—Unverified
4CONTRIQUESRCC0.84—Unverified
5HyperIQASRCC0.84—Unverified
6DB-CNNSRCC0.82—Unverified
7Re-IQASRCC0.8—Unverified
8BRISQUESRCC0.6—Unverified
#ModelMetricClaimedVerifiedStatus
1LAR-IQA (KAN head)SRCC0.84—Unverified
2QualiCLIPSRCC0.77—Unverified
3CLIP-IQA+SRCC0.75—Unverified
4ARNIQASRCC0.74—Unverified
5CONTRIQUESRCC0.73—Unverified
6Effnet-2C-MLSPSRCC0.68—Unverified
7HyperIQASRCC0.55—Unverified
#ModelMetricClaimedVerifiedStatus
1RvTC (image-only)PLCC0.95—Unverified
#ModelMetricClaimedVerifiedStatus
1UNIQASRCC0.99—Unverified
#ModelMetricClaimedVerifiedStatus
1RvTC (image-only)PLCC0.93—Unverified