Video Quality Assessment On Konvid 1K

Métriques

PLCC

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	PLCC	Paper Title	Repository
VIDEVAL	0.7803	UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content	-
RAPIQUE	0.8175	RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content	-
FAST-VQA (trained on LSVQ only)	0.855	FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling	-
2BiVQA	0.835	2BiVQA: Double Bi-LSTM based Video Quality Assessment of UGC Videos	-
ReLaX-VQA (trained on LSVQ only)	0.8427	ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing Video Quality Assessment	-
ChipQA	0.7625	ChipQA: No-Reference Video Quality Prediction via Space-Time Chips	-
FasterVQA (fine-tuned)	0.898	Neighbourhood Representative Sampling for Efficient End-to-end Video Quality Assessment	-
HVS-5M	0.8562	HVS Revisited: A Comprehensive Video Quality Assessment Framework	-
SimpleVQA	0.860	A Deep Learning based No-reference Quality Assessment Model for UGC Videos	-
DisCoVQA	0.860	DisCoVQA: Temporal Distortion-Content Transformers for Video Quality Assessment	-
CONTRIQUE	0.842	Image Quality Assessment using Contrastive Learning	-
DOVER (end-to-end)	0.905	Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives	-
VSFA	0.7754	Quality Assessment of In-the-Wild Videos	-
FAST-VQA (finetuned on KonViD-1k)	0.892	FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling	-
CONVIQT	0.849	CONVIQT: Contrastive Video Quality Estimator	-
ReLaX-VQA	0.8473	ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing Video Quality Assessment	-
DOVER (head-only)	0.894	Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives	-
TLVQM	0.7688	Two-Level Approach for No-Reference Consumer Video Quality Assessment
ReLaX-VQA (finetuned on KoNViD-1k)	0.8668	ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing Video Quality Assessment	-
PVQ	0.770	Patch-VQ: 'Patching Up' the Video Quality Problem	-

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