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

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Showing 51–100 of 155 papers

TitleStatusHype
Less is More: Learning Reference Knowledge Using No-Reference Image Quality Assessment—0
PKU-I2IQA: An Image-to-Image Quality Assessment Database for AI Generated ImagesCode1
VCISR: Blind Single Image Super-Resolution with Video Compression Synthetic DataCode1
ARNIQA: Learning Distortion Manifold for Image Quality AssessmentCode1
AutoDIR: Automatic All-in-One Image Restoration with Latent DiffusionCode1
You Only Train Once: A Unified Framework for Both Full-Reference and No-Reference Image Quality AssessmentCode0
Interpretable Image Quality Assessment via CLIP with Multiple Antonym-Prompt Pairs—0
TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality AssessmentCode4
Test Time Adaptation for Blind Image Quality AssessmentCode0
Analysis of Video Quality Datasets via Design of Minimalistic Video Quality ModelsCode1
On the Effectiveness of Spectral Discriminators for Perceptual Quality ImprovementCode1
Self2Self+: Single-Image Denoising with Self-Supervised Learning and Image Quality Assessment LossCode1
Regression-free Blind Image Quality Assessment with Content-Distortion Consistency—0
Blind Image Quality Assessment: A Fuzzy Neural Network for Opinion Score Distribution PredictionCode0
Deep learning techniques for blind image super-resolution: A high-scale multi-domain perspective evaluationCode1
Collaborative Auto-encoding for Blind Image Quality AssessmentCode0
MAMIQA: No-Reference Image Quality Assessment Based on Multiscale Attention Mechanism With Natural Scene StatisticsCode0
Blind Image Quality Assessment via Transformer Predicted Error Map and Perceptual Quality TokenCode1
Fast Adversarial CNN-based Perturbation Attack of No-Reference Image Quality MetricsCode0
Data-Efficient Image Quality Assessment with Attention-Panel DecoderCode1
Re-IQA: Unsupervised Learning for Image Quality Assessment in the WildCode1
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning PerspectiveCode2
Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable BankCode1
Subjective and Objective Quality Assessment for in-the-Wild Computer Graphics ImagesCode0
JNDMix: JND-Based Data Augmentation for No-reference Image Quality Assessment—0
PMT-IQA: Progressive Multi-task Learning for Blind Image Quality AssessmentCode0
KonX: Cross-Resolution Image Quality Assessment—0
Universal Perturbation Attack on Differentiable No-Reference Image- and Video-Quality MetricsCode1
QMRNet: Quality Metric Regression for EO Image Quality Assessment and Super-ResolutionCode0
Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-LoopCode1
Forgetting to Remember: A Scalable Incremental Learning Framework for Cross-Task Blind Image Quality AssessmentCode0
Deep Feature Statistics Mapping for Generalized Screen Content Image Quality AssessmentCode1
A Human Visual System Inspired No-Reference Image Quality Assessment Method Based on Local Feature DescriptorsCode0
REQA: Coarse-to-fine Assessment of Image Quality to Alleviate the Range EffectCode1
Exploring CLIP for Assessing the Look and Feel of ImagesCode2
No-Reference Quality Assessment of Authentically Distorted Images Based on Local and Global FeaturesCode0
Pixel-by-pixel Mean Opinion Score (pMOS) for No-Reference Image Quality Assessment—0
Subjective Quality Assessment for Images Generated by Computer Graphics—0
MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusion—0
Conformer and Blind Noisy Students for Improved Image Quality AssessmentCode1
MANIQA: Multi-dimension Attention Network for No-Reference Image Quality AssessmentCode2
UID2021: An Underwater Image Dataset for Evaluation of No-reference Quality Assessment MetricsCode0
Content-Variant Reference Image Quality Assessment via Knowledge DistillationCode1
BIQ2021: A Large-Scale Blind Image Quality Assessment Database—0
3D Saliency guided Deep Quality predictor for No-Reference Stereoscopic ImagesCode0
No-Reference Image Quality Assessment with Convolutional Neural Networks and Decision FusionCode0
No-Reference Video Quality Assessment Based on Benford’s Law and Perceptual FeaturesCode0
Image Quality Assessment using Contrastive LearningCode1
Deep Superpixel-based Network for Blind Image Quality AssessmentCode0
Analysis of Benford’s Law for No-Reference Quality Assessment of Natural, Screen-Content, and Synthetic ImagesCode0
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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