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Image Quality Assessment

Papers

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Showing 551–575 of 732 papers

TitleStatusHype
UNO-QA: An Unsupervised Anomaly-Aware Framework with Test-Time Clustering for OCTA Image Quality Assessment—0
Unsupervised Deep Contrast Enhancement with Power Constraint for OLED Displays—0
Unsupervised Multi-Clustering and Decision-Making Strategies for 4D-STEM Orientation Mapping—0
Utility-Oriented Underwater Image Quality Assessment Based on Transfer Learning—0
Video Quality Assessment Based on Swin TransformerV2 and Coarse to Fine Strategy—0
Vision Language Modeling of Content, Distortion and Appearance for Image Quality Assessment—0
Visual-Language Model Knowledge Distillation Method for Image Quality Assessment—0
Visual Mechanisms Inspired Efficient Transformers for Image and Video Quality Assessment—0
Visual question answering based evaluation metrics for text-to-image generation—0
VR IQA NET: Deep Virtual Reality Image Quality Assessment using Adversarial Learning—0
VSI: A Visual Saliency-Induced Index for Perceptual Image Quality Assessment—0
X-Fake: Juggling Utility Evaluation and Explanation of Simulated SAR Images—0
Zero-shot super-resolution with a physically-motivated downsampling kernel for endomicroscopy—0
1st Place Solutions for UG2+ Challenge 2022 ATMOSPHERIC TURBULENCE MITIGATION—0
Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data—0
Learning from Irregularly Sampled Data for Endomicroscopy Super-resolution: A Comparative Study of Sparse and Dense Approaches—0
Learning image quality assessment by reinforcing task amenable data selection—0
Learning Numerical Observers using Unsupervised Domain Adaptation—0
Learning to Rank for Blind Image Quality Assessment—0
Learning Transformer Features for Image Quality Assessment—0
Learning with Noisy Low-Cost MOS for Image Quality Assessment via Dual-Bias Calibration—0
Learning without Human Scores for Blind Image Quality Assessment—0
Learn to Evaluate Image Perceptual Quality Blindly from Statistics of Self-similarity—0
Less is More: Learning Reference Knowledge Using No-Reference Image Quality Assessment—0
Light Field Image Quality Assessment With Auxiliary Learning Based on Depthwise and Anglewise Separable Convolutions—0
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All datasetsMSU NR VQA DatabaseKonIQ-10kMSU FR VQA Database

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SPAQ MT-SSRCC0.88—Unverified
2SPAQ BLSRCC0.88—Unverified
3SPAQ MT-ASRCC0.88—Unverified
4KonCept512SRCC0.84—Unverified
5MEONSRCC0.51—Unverified
#ModelMetricClaimedVerifiedStatus
1RealQASRCC0.95—Unverified
2OneAlignSRCC0.94—Unverified
3UNIQASRCC0.93—Unverified
4KonCept512SRCC0.92—Unverified
#ModelMetricClaimedVerifiedStatus
1FSIMSRCC0.9—Unverified
2DSSSRCC0.9—Unverified
3MS-GMSDSRCC0.89—Unverified
4GMSDSRCC0.89—Unverified