HyperAI超神经

No Reference Image Quality Assessment On 1

评估指标

PLCC

SRCC

评测结果

各个模型在此基准测试上的表现结果

			Paper Title
UNIQA	0.946	0.944	You Only Train Once: A Unified Framework for Both Full-Reference and No-Reference Image Quality Assessment
CONTRIQUE	0.937	0.934	Image Quality Assessment using Contrastive Learning
ARNIQA	0.912	0.908	ARNIQA: Learning Distortion Manifold for Image Quality Assessment
Re-IQA	0.885	0.872	Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild
TReS	0.858	0.859	No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency
DB-CNN	0.856	0.851	Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
HyperIQA	0.845	0.852	Blindly Assess Image Quality in the Wild Guided by a Self-Adaptive Hyper Network
BRISQUE	0.567	0.528	No-Reference Image Quality Assessment in the Spatial Domain

0 of 8 row(s) selected.

HyperAI超神经

No Reference Image Quality Assessment On 1

评估指标

PLCC

SRCC

评测结果

各个模型在此基准测试上的表现结果

			Paper Title
UNIQA	0.946	0.944	You Only Train Once: A Unified Framework for Both Full-Reference and No-Reference Image Quality Assessment
CONTRIQUE	0.937	0.934	Image Quality Assessment using Contrastive Learning
ARNIQA	0.912	0.908	ARNIQA: Learning Distortion Manifold for Image Quality Assessment
Re-IQA	0.885	0.872	Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild
TReS	0.858	0.859	No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency
DB-CNN	0.856	0.851	Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
HyperIQA	0.845	0.852	Blindly Assess Image Quality in the Wild Guided by a Self-Adaptive Hyper Network
BRISQUE	0.567	0.528	No-Reference Image Quality Assessment in the Spatial Domain

0 of 8 row(s) selected.

No Reference Image Quality Assessment On 1 | SOTA | HyperAI超神经