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Video Quality Assessment On Live Fb Lsvq

Métriques

PLCC

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
PLCC
Paper TitleRepository
CONTRIQUE0.826Image Quality Assessment using Contrastive Learning-
DisCoVQA0.850DisCoVQA: Temporal Distortion-Content Transformers for Video Quality Assessment-
CONVIQT0.820CONVIQT: Contrastive Video Quality Estimator-
FasterVQA0.874Neighbourhood Representative Sampling for Efficient End-to-end Video Quality Assessment-
DOVER0.889Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives-
VIDEVAL0.783UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content-
HVS-5M0.8723HVS Revisited: A Comprehensive Video Quality Assessment Framework-
OneAlign0.886Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels-
PVQ0.827Patch-VQ: 'Patching Up' the Video Quality Problem-
OneAlign + FAST-VQA0.900Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels-
SimpleVQA0.861A Deep Learning based No-reference Quality Assessment Model for UGC Videos-
BVQA-20220.854Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion Perception-
FAST-VQA0.877FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling-
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Video Quality Assessment On Live Fb Lsvq | SOTA | HyperAI