Video Salient Object Detection On Vos T
Métriques
Average MAE
S-Measure
max E-measure
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Average MAE | S-Measure | max E-measure | Paper Title | Repository |
|---|---|---|---|---|---|
| MB+M | 0.158 | 0.661 | 0.698 | Minimum Barrier Salient Object Detection at 80 FPS | - |
| RCRNet+NER | 0.049 | 0.872 | 0.856 | Semi-Supervised Video Salient Object Detection Using Pseudo-Labels | |
| SAGM | 0.172 | 0.615 | 0.664 | Saliency-Aware Geodesic Video Object Segmentation | - |
| MSTM | 0.144 | 0.657 | 0.695 | Real-Time Salient Object Detection With a Minimum Spanning Tree | |
| PDB | 0.078 | 0.818 | 0.837 | Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection | - |
| FGRN | 0.097 | 0.715 | 0.797 | Flow Guided Recurrent Neural Encoder for Video Salient Object Detection | - |
| TIMP | 0.192 | 0.546 | 0.640 | Time-Mapping Using Space-Time Saliency | - |
| MBNM | 0.099 | 0.742 | 0.797 | Unsupervised Video Object Segmentation with Motion-based Bilateral Networks | - |
| SSAV | 0.074 | 0.819 | 0.839 | Shifting More Attention to Video Salient Object Detection |
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