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Video Quality Assessment On Msu Video Quality 1

Métriques

KLCC
SRCC

Résultats

Résultats de performance de divers modèles sur ce benchmark

Paper Title
VMAF Y (v062)0.8090.942Toward A Practical Perceptual Video Quality Metric
VMAF Y (v061)0.8090.942Toward A Practical Perceptual Video Quality Metric
VMAF Y (v063)0.8090.942Toward A Practical Perceptual Video Quality Metric
AHIQ0.80150.937Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network
VMAF Y (v061_neg)0.7650.914Toward A Practical Perceptual Video Quality Metric
MS-SSIM0.76250.9026Multiscale structural similarity for image quality assessment
SSIM0.76150.8999Image quality assessment: from error visibility to structural similarity
VIFp0.75580.9079Image information and visual quality
VSI0.75240.9053VSI: A Visual Saliency-Induced Index for Perceptual Image Quality Assessment
AVQT0.74990.8920-
SR-SIM0.74720.9014SR-SIM: A fast and high performance IQA index based on spectral residual
HaarPSI0.74510.8982A Haar Wavelet-Based Perceptual Similarity Index for Image Quality Assessment
FSIM0.74180.9000FSIM: A Feature Similarity Index for Image Quality Assessment
MDSI0.73790.8971Mean Deviation Similarity Index: Efficient and Reliable Full-Reference Image Quality Evaluator
PSNR0.71850.8668-
FR GVSP-UGCVQA (single scale)0.6950.864Deep Learning based Full-reference and No-reference Quality Assessment Models for Compressed UGC Videos
DVQA0.61060.7810-
ST-GREED0.59050.7547ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality Prediction
LPIPS0.58460.7538The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
FovVideoVDP0.3820.537FovVideoVDP: A visible difference predictor for wide field-of-view video
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Video Quality Assessment On Msu Video Quality 1 | SOTA | HyperAI