SOTAVerified

Full reference image quality assessment

The goal is to calculate an objective quality score for a given (potentially) distorted image given its reference (potentially) pristine quality image is available. Training-free metrics are listed.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–50 of 50 papers

TitleStatusHype
Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality AssumptionCode2
Mean Deviation Similarity Index: Efficient and Reliable Full-Reference Image Quality EvaluatorCode2
Sliced Maximal Information Coefficient: A Training-Free Approach for Image Quality Assessment EnhancementCode1
A combined full-reference image quality assessment approach based on convolutional activation mapsCode1
PKU-I2IQA: An Image-to-Image Quality Assessment Database for AI Generated ImagesCode1
Perceptual Image Quality Assessment with TransformersCode1
SwinIQA: Learned Swin Distance for Compressed Image Quality AssessmentCode1
The Unreasonable Effectiveness of Linear Prediction as a Perceptual MetricCode1
Deep Learning of Human Visual Sensitivity in Image Quality Assessment FrameworkCode1
Saliency-Guided Local Full-Reference Image Quality AssessmentCode0
Deep Neural Networks for No-Reference and Full-Reference Image Quality AssessmentCode0
Multiscale structural similarity for image quality assessmentCode0
Foundation Models Boost Low-Level Perceptual Similarity MetricsCode0
Quality Aware Generative Adversarial NetworksCode0
FSIM: A Feature Similarity Index for Image Quality Assessment—0
Full-reference image quality assessment-based B-mode ultrasound image similarity measure—0
Full-reference image quality assessment by combining global and local distortion measures—0
Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index—0
Image information and visual quality—0
Image quality assessment based on DCT subband similarity—0
Image Quality Assessment: Enhancing Perceptual Exploration and Interpretation with Collaborative Feature Refinement and Hausdorff distance—0
Image quality assessment: from error visibility to structural similarity—0
Image Quality Assessment: Investigating Causal Perceptual Effects with Abductive Counterfactual Inference—0
Image Quality Assessment with Gradient Siamese Network—0
Incorporating Semi-Supervised and Positive-Unlabeled Learning for Boosting Full Reference Image Quality Assessment—0
Information Content Weighting for Perceptual Image Quality Assessment—0
Locally Adaptive Structure and Texture Similarity for Image Quality Assessment—0
Most Apparent Distortion: Full-Reference Image Quality Assessment and the Role of Strategy—0
Perceptual Error Logarithm: An Efficient and Effective Analytical Method for Full-Reference Image Quality Assessment—0
Perceptual Quality Assessment for Fine-Grained Compressed Images—0
Perceptual Quality Assessment for Video Frame Interpolation—0
Sparse Feature Fidelity for Perceptual Image Quality Assessment—0
SR-SIM: A fast and high performance IQA index based on spectral residual—0
Subjective and Objective Quality Assessment of Image: A Survey—0
Subjective Image Quality Assessment with Boosted Triplet Comparisons—0
Training-Free Synthesized Face Sketch Recognition Using Image Quality Assessment Metrics—0
VSI: A Visual Saliency-Induced Index for Perceptual Image Quality Assessment—0
A comprehensive evaluation of full-reference image quality assessment algorithms on KADID-10k—0
A Haar Wavelet-Based Perceptual Similarity Index for Image Quality Assessment—0
A Shift-insensitive Full Reference Image Quality Assessment Model Based on Quadratic Sum of Gradient Magnitude and LOG signals—0
A study of why we need to reassess full reference image quality assessment with medical images—0
A survey on IQA—0
BELE: Blur Equivalent Linearized Estimator—0
Blind Predicting Similar Quality Map for Image Quality Assessment—0
Center Emphasized Visual Saliency and a Contrast-based Full Reference Image Quality Index—0
Contrast and visual saliency similarity-induced index for assessing image quality—0
Deep Optimization model for Screen Content Image Quality Assessment using Neural Networks—0
Deviation Based Pooling Strategies For Full Reference Image Quality Assessment—0
Digital twins enable full-reference quality assessment of photoacoustic image reconstructions—0
Evaluation of quality measures for color quantization—0
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All datasetsTID2008ESPLKADID10KDRIQ

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MDSISRCC0.92—Unverified
2HaarPSISRCC0.91—Unverified
3IQA MetricSRCC0.9—Unverified
4VSISRCC0.9—Unverified
5SR-SIMSRCC0.89—Unverified
6GMSDSRCC0.89—Unverified
7FSIMcSRCC0.88—Unverified
8SFFSRCC0.88—Unverified
9IW-SSIMSRCC0.86—Unverified
10MS-SSIMSRCC0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1MDSISRCC0.88—Unverified
2SR-SIMSRCC0.88—Unverified
3FSIMcSRCC0.88—Unverified
4VSISRCC0.87—Unverified
5MADSRCC0.86—Unverified
6HaarPSISRCC0.85—Unverified
7IW-SSIMSRCC0.83—Unverified
8GMSDSRCC0.82—Unverified
9SFFSRCC0.81—Unverified
10VIFSRCC0.75—Unverified
#ModelMetricClaimedVerifiedStatus
1MDSISRCC0.89—Unverified
2HaarPSISRCC0.88—Unverified
3VSISRCC0.88—Unverified
4PELSRCC0.88—Unverified
5FSIMcSRCC0.85—Unverified
6GMSDSRCC0.85—Unverified
7SR-SIMSRCC0.84—Unverified
8FSIMSRCC0.83—Unverified
9MS-SSIMSRCC0.8—Unverified
10VIFSRCC0.65—Unverified
#ModelMetricClaimedVerifiedStatus
1MDSISRCC0.85—Unverified
2SFFSRCC0.83—Unverified
3VSISRCC0.82—Unverified
4VIFSRCC0.81—Unverified
5GMSDSRCC0.78—Unverified
6FSIMcSRCC0.78—Unverified
7SR-SIMSRCC0.76—Unverified
8IW-SSIMSRCC0.69—Unverified
9MADSRCC0.69—Unverified
10MS-SSIMSRCC0.67—Unverified