Video Salient Object Detection On Davsod
Métriques
Average MAE
S-Measure
max E-Measure
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Average MAE | S-Measure | max E-Measure |
|---|---|---|---|
| time-mapping-using-space-time-saliency | 0.206 | 0.534 | 0.582 |
| shifting-more-attention-to-video-salient | 0.084 | 0.755 | 0.806 |
| unsupervised-video-object-segmentation-with-1 | 0.109 | 0.646 | 0.694 |
| flow-guided-recurrent-neural-encoder-for | 0.095 | 0.701 | 0.765 |
| saliency-aware-geodesic-video-object | 0.187 | 0.564 | 0.640 |
| transforming-static-images-using-generative | 0.066 | 0.803 | - |
| pyramid-dilated-deeper-convlstm-for-video | 0.114 | 0.706 | 0.749 |
| minimum-barrier-salient-object-detection-at | 0.231 | 0.536 | 0.624 |
| real-time-salient-object-detection-with-a | 0.214 | 0.530 | 0.632 |