Saliency Prediction on MIT300 (test)
0.82CCDPNSal
Evaluation results
| Method | Links | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| DPNSalLearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.82 | 0.74 | — | 2.41 | 0.87 | 0.69 | 0.91 | 2.05 | 0.8 | |
| TranSalNet_DenseBackbone=DenseNet2021.10 | 0.807 | 0.7467 | 0.8734 | 2.4134 | — | 0.6895 | 1.0141 | — | — | |
| DSCLRCN2019.04 | 0.8 | 0.72 | 0.87 | 2.35 | — | — | — | — | — | |
| DSCLRCNLearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.8 | 0.72 | — | 2.35 | 0.87 | 0.68 | 0.95 | 2.17 | 0.79 | |
| TranSalNet_ResBackbone=ResNet2021.10 | 0.7991 | 0.7471 | 0.873 | 2.3758 | — | 0.6852 | 0.9019 | — | — | |
| DINet2019.04 | 0.79 | 0.71 | 0.86 | 2.33 | — | — | — | — | — | |
| DINet2020.03 | 0.79 | 0.71 | — | 2.33 | 0.86 | — | — | — | — | |
| DenseSalLearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.79 | 0.72 | — | 2.25 | 0.87 | 0.67 | 0.48 | 1.99 | 0.81 | |
| EML-NETLearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.79 | 0.7 | — | 2.47 | 0.88 | 0.68 | 0.84 | 1.84 | 0.77 | |
| MSI-NetLearning Paradigm=Deep Learning2019.02 | 0.79 | 0.72 | — | 2.27 | 0.87 | 0.68 | 0.66 | 1.99 | 0.82 | |
| HATES2021.10 | 0.7897 | 0.7549 | 0.8744 | 2.3762 | — | 0.5313 | 0.7146 | — | — | |
| EML-NET2021.10 | 0.7893 | 0.7469 | 0.8762 | 2.4876 | — | 0.6756 | 0.8439 | — | — | |
| UNISALTraining setting=(vi)2020.03 | 0.784 | 0.743 | — | 2.322 | 0.872 | 0.674 | — | — | — | |
| SAMBackbone=ResNet2019.04 | 0.78 | 0.7 | 0.87 | 2.34 | — | — | — | — | — | |
| DeepFix2019.04 | 0.78 | 0.71 | 0.87 | 2.26 | — | — | — | — | — | |
| SAM-ResNet2020.03 | 0.78 | 0.7 | — | 2.34 | 0.87 | 0.68 | — | — | — | |
| DeepFixLearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.78 | 0.71 | — | 2.26 | 0.87 | 0.67 | 0.63 | 2.04 | 0.8 | |
| SAM-ResNetLearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.78 | 0.7 | — | 2.34 | 0.87 | 0.68 | 1.27 | 2.15 | 0.78 | |
| SAMBackbone=VGG2019.04 | 0.77 | 0.71 | 0.87 | 2.3 | — | — | — | — | — | |
| SAM-VGGLearning Paradigm=Deep Learning, Backbone Architecture=VGG16, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.77 | 0.71 | — | 2.3 | 0.87 | 0.67 | 1.13 | 2.14 | 0.78 | |
| GazeGAN2021.10 | 0.7579 | 0.7316 | 0.8607 | 2.2118 | — | 0.6491 | 1.339 | — | — | |
| SALICON2019.04 | 0.74 | 0.74 | 0.87 | 2.12 | — | — | — | — | — | |
| SALICON2020.03 | 0.74 | 0.74 | — | 2.12 | 0.87 | 0.6 | — | — | — | |
| SALICONLearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.74 | 0.74 | — | 2.12 | 0.87 | 0.6 | 0.54 | 2.62 | 0.85 | |
| SalGAN2019.04 | 0.73 | 0.72 | 0.86 | 2.04 | — | — | — | — | — | |
| SalGAN2020.03 | 0.73 | 0.72 | — | 2.04 | 0.86 | 0.63 | — | — | — | |
| CASNet II2021.10 | 0.7054 | 0.7398 | 0.8552 | 1.9859 | — | 0.5806 | 0.5857 | — | — | |
| PDP2019.04 | 0.7 | 0.73 | 0.85 | 2.05 | — | — | — | — | — | |
| Deep-Net2020.03 | 0.69 | — | — | — | 0.83 | 0.52 | — | — | — | |
| SAM-ResNetBackbone=ResNet2021.10 | 0.6897 | 0.7396 | 0.8526 | 2.0628 | — | 0.6122 | 1.171 | — | — | |
| DVA2019.04 | 0.68 | 0.71 | 0.85 | 1.98 | — | — | — | — | — | |
| DVA2020.03 | 0.68 | 0.71 | — | 1.98 | 0.85 | 0.58 | — | — | — | |
| SalGAN2021.10 | 0.674 | 0.7354 | 0.8498 | 1.862 | — | 0.5932 | 0.7574 | — | — | |
| ML-Net2019.04 | 0.67 | 0.7 | 0.85 | 2.05 | — | — | — | — | — | |
| ML-NetLearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.67 | 0.7 | — | 2.05 | 0.85 | 0.59 | 1.1 | 2.63 | 0.75 | |
| ML-Net2021.10 | 0.6633 | 0.7399 | 0.8386 | 1.9748 | — | 0.5819 | 0.8006 | — | — | |
| DVA2021.10 | 0.6631 | 0.7257 | 0.843 | 1.9305 | — | 0.5848 | 0.6293 | — | — | |
| SAM-VGGBackbone=VGG2021.10 | 0.663 | 0.7305 | 0.8473 | 1.9552 | — | 0.5986 | 1.2746 | — | — | |
| SalNet2019.04 | 0.58 | 0.69 | 0.83 | 1.51 | — | — | — | — | — | |
| BMS2019.04 | 0.55 | 0.65 | 0.83 | 1.41 | — | — | — | — | — | |
| Shallow-Net2020.03 | 0.53 | 0.64 | — | — | 0.8 | 0.46 | — | — | — | |
| DeepGazeII2019.04 | 0.52 | 0.72 | 0.88 | 1.29 | — | — | — | — | — | |
| DeepGaze IILearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.52 | 0.72 | — | 1.29 | 0.88 | 0.46 | 0.96 | 3.98 | 0.86 | |
| GBVS2019.04 | 0.48 | 0.63 | 0.81 | 1.24 | — | — | — | — | — | |
| Mr-CNN2019.04 | 0.48 | 0.69 | 0.79 | 1.37 | — | — | — | — | — | |
| GBVS2020.03 | 0.48 | 0.63 | — | 1.24 | 0.81 | 0.48 | — | — | — | |
| DeepGaze ILearning Paradigm=Deep Learning, Pre-training Strategy=Pre-trained on image classification2019.02 | 0.48 | 0.66 | — | 1.22 | 0.84 | 0.39 | 1.23 | 4.97 | 0.83 | |
| GBVSLearning Paradigm=Shallow networks and other machine learning2019.02 | 0.48 | 0.63 | — | 1.24 | 0.81 | 0.48 | 0.87 | 3.51 | 0.8 | |
| JuddLearning Paradigm=Theoretical considerations/Baseline2019.02 | 0.47 | 0.6 | — | 1.18 | 0.81 | 0.42 | 1.12 | 4.45 | 0.8 | |
| eDN2021.10 | 0.4518 | 0.618 | 0.8171 | 1.1399 | — | 0.4112 | 1.1369 | — | — | |
| eDN2019.04 | 0.45 | 0.62 | 0.82 | 1.14 | — | — | — | — | — | |
| eDNLearning Paradigm=Theoretical considerations/Baseline2019.02 | 0.45 | 0.62 | — | 1.14 | 0.82 | 0.41 | 1.14 | 4.56 | 0.81 | |
| ITTI2019.04 | 0.37 | 0.63 | 0.75 | 0.97 | — | — | — | — | — | |
| ITTI2020.03 | 0.37 | 0.63 | — | 0.97 | 0.75 | 0.44 | — | — | — | |
| IttiLearning Paradigm=Shallow networks and other machine learning2019.02 | 0.37 | 0.63 | — | 0.97 | 0.75 | 0.44 | 1.03 | 4.26 | 0.74 | |
| SUNLearning Paradigm=Shallow networks and other machine learning2019.02 | 0.25 | 0.61 | — | 0.68 | 0.67 | 0.38 | 1.27 | 5.1 | 0.66 |