No Reference Image Quality Assessment On
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
模型名称 | PLCC | SRCC | Paper Title | Repository |
|---|---|---|---|---|
| Re-IQA | 0.861 | 0.804 | Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild | |
| ARNIQA | 0.901 | 0.880 | ARNIQA: Learning Distortion Manifold for Image Quality Assessment | |
| TReS | 0.883 | 0.863 | No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency | |
| BRISQUE | 0.694 | 0.604 | No-Reference Image Quality Assessment in the Spatial Domain | - |
| UNIQA | 0.956 | 0.953 | You Only Train Once: A Unified Framework for Both Full-Reference and No-Reference Image Quality Assessment | |
| CONTRIQUE | 0.857 | 0.843 | Image Quality Assessment using Contrastive Learning | |
| DB-CNN | 0.865 | 0.816 | Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network | |
| HyperIQA | 0.858 | 0.840 | Blindly Assess Image Quality in the Wild Guided by a Self-Adaptive Hyper Network | - |
0 of 8 row(s) selected.