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Image Quality Assessment

Papers

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Showing 301–350 of 732 papers

TitleStatusHype
Causal Perception Inspired Representation Learning for Trustworthy Image Quality Assessment—0
PKU-AIGIQA-4K: A Perceptual Quality Assessment Database for Both Text-to-Image and Image-to-Image AI-Generated ImagesCode0
Assessing Image Quality Using a Simple Generative RepresentationCode0
Image Quality Assessment With Compressed Sampling—0
NTIRE 2024 Quality Assessment of AI-Generated Content Challenge—0
Adaptive Mixed-Scale Feature Fusion Network for Blind AI-Generated Image Quality Assessment—0
Multi-Modal Prompt Learning on Blind Image Quality AssessmentCode0
CrossScore: Towards Multi-View Image Evaluation and Scoring—0
Beyond Score Changes: Adversarial Attack on No-Reference Image Quality Assessment from Two Perspectives—0
PCQA: A Strong Baseline for AIGC Quality Assessment Based on Prompt Condition—0
Multi-Sensor Diffusion-Driven Optical Image Translation for Large-Scale Applications—0
AI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge DistillationCode0
PHISWID: Physics-Inspired Underwater Image Dataset Synthesized from RGB-D ImagesCode0
AIGIQA-20K: A Large Database for AI-Generated Image Quality Assessment—0
AIGCOIQA2024: Perceptual Quality Assessment of AI Generated Omnidirectional ImagesCode0
An edge detection-based deep learning approach for tear meniscus height measurement—0
Quality-Aware Image-Text Alignment for Real-World Image Quality AssessmentCode0
Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment—0
IG-FIQA: Improving Face Image Quality Assessment through Intra-class Variance Guidance robust to Inaccurate Pseudo-LabelsCode0
When No-Reference Image Quality Models Meet MAP Estimation in Diffusion Latents—0
Black-box Adversarial Attacks Against Image Quality Assessment Models—0
Accelerated Real-time Cine and Flow under In-magnet Staged Exercise—0
Towards Open-ended Visual Quality Comparison—0
A Lightweight Parallel Framework for Blind Image Quality Assessment—0
Data Quality Aware Approaches for Addressing Model Drift of Semantic Segmentation Models—0
Quantitative Metrics for Benchmarking Medical Image Harmonization—0
Compressed image quality assessment using stacking—0
A New Image Quality Database for Multiple Industrial Processes—0
Double Trouble? Impact and Detection of Duplicates in Face Image DatasetsCode0
Feature Denoising Diffusion Model for Blind Image Quality Assessment—0
GMC-IQA: Exploiting Global-correlation and Mean-opinion Consistency for No-reference Image Quality Assessment—0
Deep Shape-Texture Statistics for Completely Blind Image Quality Evaluation—0
Video Quality Assessment Based on Swin TransformerV2 and Coarse to Fine Strategy—0
Progressive Feature Fusion Network for Enhancing Image Quality Assessment—0
Exploring Vulnerabilities of No-Reference Image Quality Assessment Models: A Query-Based Black-Box Method—0
Blind Image Quality Assessment: A Brief Survey—0
IQAGPT: Image Quality Assessment with Vision-language and ChatGPT Models—0
Perceptual Quality Assessment for Video Frame Interpolation—0
Q-Boost: On Visual Quality Assessment Ability of Low-level Multi-Modality Foundation Models—0
Robust Sclera Segmentation for Skin-tone Agnostic Face Image Quality AssessmentCode0
IQNet: Image Quality Assessment Guided Just Noticeable Difference Prefiltering For Versatile Video Coding—0
Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivity—0
PSCR: Patches Sampling-based Contrastive Regression for AIGC Image Quality AssessmentCode0
Less is More: Learning Reference Knowledge Using No-Reference Image Quality Assessment—0
FS-BAND: A Frequency-Sensitive Banding Detector—0
Joint Deep Image Restoration and Unsupervised Quality Assessment—0
Learning with Noisy Low-Cost MOS for Image Quality Assessment via Dual-Bias Calibration—0
Quality Modeling Under A Relaxed Natural Scene Statistics Model—0
Perceptual Image Compression with Cooperative Cross-Modal Side Information—0
Astronomical Images Quality Assessment with Automated Machine Learning—0
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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