No-Reference Image Quality Assessment on TID 2013
0.956SRCCOurs-S+
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| Ours-S+Backbone=Swin-Tiny, Joint training (FR & NR tasks)=true, Architecture Type=Transformer-based2023.10 | 0.956 | 0.958 | |
| Ours-SBackbone=Swin-Tiny, Joint training (FR & NR tasks)=false, Architecture Type=Transformer-based2023.10 | 0.953 | 0.956 | |
| Re-IQAModule=content + quality2023.04 | 0.947 | 0.96 | |
| DB-CNN2023.04 | 0.946 | 0.959 | |
| Re-IQAModule=quality-aware2023.04 | 0.944 | 0.964 | |
| CONTRIQUE2023.04 | 0.942 | 0.955 | |
| MANIQAArchitecture Type=Transformer-based2023.10 | 0.937 | 0.943 | |
| HyperIQA2023.04 | 0.923 | 0.942 | |
| SHAMISAType=SSL+LR2026.03 | 0.904 | 0.919 | |
| Ours-RBackbone=ResNet50, Joint training (FR & NR tasks)=false2023.10 | 0.902 | 0.908 | |
| SLIDE-IQA2026.06 | 0.899 | 0.911 | |
| SLIDE-IQA-Q2026.06 | 0.881 | 0.892 | |
| ARNIQAType=SSL+LR2026.03 | 0.88 | 0.901 | |
| ARNIQA2026.06 | 0.88 | 0.901 | |
| TRESArchitecture Type=CNN/Hand-crafted2023.10 | 0.863 | 0.883 | |
| TReSType=Supervised2026.03 | 0.863 | 0.883 | |
| TReS2026.06 | 0.863 | 0.883 | |
| P2P-BMArchitecture Type=CNN/Hand-crafted2023.10 | 0.862 | 0.856 | |
| MetaIQAArchitecture Type=CNN/Hand-crafted2023.10 | 0.856 | 0.868 | |
| TIQAArchitecture Type=Transformer-based2023.10 | 0.846 | 0.858 | |
| ReIQA-Q2026.06 | 0.844 | 0.88 | |
| CONTRIQUEType=SSL+LR2026.03 | 0.843 | 0.857 | |
| CONTRIQUE2026.06 | 0.843 | 0.857 | |
| ImageNet Pretrained (Supervised)2023.04 | 0.84 | 0.848 | |
| HyperIQAArchitecture Type=CNN/Hand-crafted2023.10 | 0.84 | 0.858 | |
| HyperIQAType=Supervised2026.03 | 0.84 | 0.858 | |
| HyperIQA2026.06 | 0.84 | 0.858 | |
| WaDIQaMArchitecture Type=CNN/Hand-crafted2023.10 | 0.835 | 0.855 | |
| MM-IQA2026.04 | 0.83 | 0.845 | |
| DBCNNArchitecture Type=CNN/Hand-crafted2023.10 | 0.816 | 0.865 | |
| DB-CNNType=Supervised2026.03 | 0.816 | 0.865 | |
| DB-CNN2026.06 | 0.816 | 0.865 | |
| Su et al.Type=Supervised2026.03 | 0.815 | 0.859 | |
| MEONArchitecture Type=CNN/Hand-crafted2023.10 | 0.808 | 0.824 | |
| Re-IQAType=SSL+LR2026.03 | 0.804 | 0.861 | |
| ReIQA2026.06 | 0.804 | 0.861 | |
| SHAMISATraining Dataset=KADID-10K2026.03 | 0.779 | — | |
| Re-IQATraining=KADID2023.10 | 0.777 | — | |
| Re-IQATraining Dataset=KADID-10K2026.03 | 0.777 | — | |
| Re-IQAModule=content-aware2023.04 | 0.766 | 0.824 | |
| ARNIQATraining=KADID2023.10 | 0.76 | — | |
| ARNIQATraining Dataset=KADID-10K2026.03 | 0.76 | — | |
| BRISQUE2023.04 | 0.746 | 0.829 | |
| PQR2026.06 | 0.74 | 0.798 | |
| HOSAType=Codebook2026.03 | 0.735 | 0.815 | |
| SHAMISATraining Dataset=CSIQ2026.03 | 0.729 | — | |
| ARNIQATraining=CSIQ2023.10 | 0.721 | — | |
| ARNIQATraining Dataset=CSIQ2026.03 | 0.721 | — | |
| BIECONArchitecture Type=CNN/Hand-crafted2023.10 | 0.717 | 0.762 | |
| HyperIQATraining=KADID2023.10 | 0.706 | — | |
| HyperIQATraining Dataset=KADID-10K2026.03 | 0.706 | — | |
| SHAMISATraining Dataset=LIVE2026.03 | 0.7 | — | |
| ARNIQATraining=LIVE2023.10 | 0.697 | — | |
| ARNIQATraining Dataset=LIVE2026.03 | 0.697 | — | |
| Su et al.Training=KADID2023.10 | 0.687 | — | |
| Su et al.Training Dataset=KADID-10K2026.03 | 0.687 | — | |
| CORNIA2023.04 | 0.678 | 0.776 | |
| CORNIAType=Codebook2026.03 | 0.678 | 0.768 | |
| CORNIA2026.06 | 0.678 | 0.768 | |
| SLIDE-IQA-CBackbone=DINOv32026.06 | 0.666 | 0.757 | |
| ReIQA-CBackbone=MoCov22026.06 | 0.658 | 0.736 | |
| DIIVINEArchitecture Type=CNN/Hand-crafted2023.10 | 0.643 | 0.567 | |
| CONTRIQUETraining=LIVE2023.10 | 0.64 | — | |
| CONTRIQUETraining Dataset=LIVE2026.03 | 0.64 | — | |
| NBIQA2026.04 | 0.628 | 0.695 | |
| GM-LOG-BIQA2026.04 | 0.627 | 0.662 | |
| BRISQUEArchitecture Type=CNN/Hand-crafted2023.10 | 0.626 | 0.571 | |
| ME-IQABase VLM=EvoQuality2026.03 | 0.619 | 0.643 | |
| CONTRIQUETraining=KADID2023.10 | 0.612 | — | |
| CONTRIQUETraining Dataset=KADID-10K2026.03 | 0.612 | — | |
| EvoQualityModel Category=VLM-based, Zero-shot evaluation=true, Evolution Round=Round 22025.09 | 0.611 | 0.674 | |
| BRISQUEType=Handcrafted2026.03 | 0.604 | 0.694 | |
| BRISQUE2026.06 | 0.604 | 0.694 | |
| Re-IQATraining=LIVE2023.10 | 0.588 | — | |
| Re-IQATraining Dataset=LIVE2026.03 | 0.588 | — | |
| EvoQualityModel Category=VLM-based, Zero-shot evaluation=true, Evolution Round=Round 12025.09 | 0.587 | 0.624 | |
| BMPRI2026.04 | 0.583 | 0.692 | |
| BaselineBase VLM=EvoQuality2026.03 | 0.581 | 0.615 | |
| Re-IQATraining=CSIQ2023.10 | 0.575 | — | |
| Re-IQATraining Dataset=CSIQ2026.03 | 0.575 | — | |
| CONTRIQUETraining=CSIQ2023.10 | 0.57 | — | |
| CONTRIQUETraining Dataset=CSIQ2026.03 | 0.57 | — | |
| Su et al.Training=LIVE2023.10 | 0.561 | — | |
| Su et al.Training Dataset=LIVE2026.03 | 0.561 | — | |
| Su et al.Training=CSIQ2023.10 | 0.55 | — | |
| Su et al.Training Dataset=CSIQ2026.03 | 0.55 | — | |
| ENIQA2026.04 | 0.545 | 0.596 | |
| HyperIQATraining=LIVE2023.10 | 0.541 | — | |
| HyperIQATraining=CSIQ2023.10 | 0.541 | — | |
| HyperIQATraining Dataset=LIVE2026.03 | 0.541 | — | |
| HyperIQATraining Dataset=CSIQ2026.03 | 0.541 | — | |
| ILNIQEArchitecture Type=CNN/Hand-crafted2023.10 | 0.521 | 0.648 | |
| SSEQ2026.04 | 0.52 | 0.615 | |
| ME-IQABase VLM=Q-Insight2026.03 | 0.508 | 0.52 | |
| BLIINDS-II2026.04 | 0.49 | 0.521 | |
| DIIVINE2026.04 | 0.487 | 0.521 | |
| CurveletQA2026.04 | 0.471 | 0.56 | |
| Q-InsightModel Category=VLM-based, Zero-shot evaluation=true2025.09 | 0.468 | 0.483 | |
| BaselineBase VLM=Q-Insight2026.03 | 0.463 | 0.477 | |
| Compare2ScoreModel Type=Non-reasoning2026.03 | 0.456 | 0.419 |