Salient Object Detection On Duts Te
Métriques
MAE
S-Measure
max F-measure
mean E-Measure
mean F-Measure
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | MAE | S-Measure | max F-measure | mean E-Measure | mean F-Measure |
|---|---|---|---|---|---|
| detect-globally-refine-locally-a-novel | 0.049 | 0.846 | 0.828 | 0.887 | 0.790 |
| bilateral-reference-for-high-resolution | 0.018 | 0.942 | 0.942 | 0.961 | 0.925 |
| saliency-detection-via-global-context | 0.048 | 0.871 | 0.859 | - | - |
| m-3-net-multilevel-mixed-and-multistage | 0.036 | 0.897 | - | - | - |
| amulet-aggregating-multi-level-convolutional | 0.075 | - | 0.773 | - | - |
| c-4-net-contextual-compression-and | 0.029 | - | - | 0.937 | 0.886 |
| picanet-learning-pixel-wise-contextual | 0.050 | 0.842 | 0.863 | 0.853 | 0.757 |
| dhsnet-deep-hierarchical-saliency-network-for | 0.065 | - | 0.815 | - | - |
| uncertainty-inspired-rgb-d-saliency-detection | 0.034 | 0.888 | - | 0.927 | 0.860 |
| cpdr-towards-highly-efficient-salient-object | 0.034 | - | - | 0.931 | 0.853 |
| instance-level-salient-object-segmentation | 0.062 | - | 0.824 | - | - |
| m-3-net-multilevel-mixed-and-multistage | 0.024 | 0.927 | - | - | - |
| bilateral-reference-for-high-resolution | 0.019 | 0.939 | 0.937 | 0.958 | 0.919 |
| tracer-extreme-attention-guided-salient | 0.022 | 0.919 | 0.932 | - | 0.904 |
| bilateral-reference-for-high-resolution | 0.018 | 0.944 | 0.943 | 0.962 | 0.925 |
| deeply-supervised-salient-object-detection | 0.065 | - | 0.813 | - | - |
| bilateral-reference-for-high-resolution | 0.018 | 0.938 | 0.935 | 0.960 | 0.923 |
| uncertainty-inspired-rgb-d-saliency-detection | 0.034 | 0.890 | - | 0.931 | 0.864 |
| non-local-deep-features-for-salient-object | 0.065 | - | 0.816 | - | - |
| a-stagewise-refinement-model-for-detecting | 0.058 | - | 0.826 | - | - |
| learning-uncertain-convolutional-features-for | 0.116 | - | 0.771 | - | - |
| tracer-extreme-attention-guided-salient | 0.035 | - | - | - | - |
| p2t-pyramid-pooling-transformer-for-scene | 0.029 | - | 0.912 | - | - |
| revisiting-image-pyramid-structure-for-high | 0.024 | 0.931 | 0.892 | - | - |
| a-weakly-supervised-learning-framework-for | 0.05 | 0.837 | - | - | - |
| a-simple-pooling-based-design-for-real-time | 0.036 | - | 0.892 | - | - |
| deep-contrast-learning-for-salient-object | 0.081 | - | 0.786 | - | - |
| bilateral-reference-for-high-resolution | 0.020 | 0.933 | 0.928 | 0.954 | 0.913 |
| basnet-boundary-aware-salient-object | 0.047 | 0.876 | - | 0.896 | 0.823 |
| progressive-attention-guided-recurrent | 0.055 | - | 0.854 | - | - |
| p2t-pyramid-pooling-transformer-for-scene | 0.033 | - | 0.895 | - | - |