Video Salient Object Detection On Visal
Metrics
Average MAE
S-Measure
max E-measure
Results
Performance results of various models on this benchmark
| Paper Title | ||||
|---|---|---|---|---|
| TIMP | 0.170 | 0.612 | 0.743 | Time-Mapping Using Space-Time Saliency |
| MB+M | 0.129 | 0.726 | 0.832 | Minimum Barrier Salient Object Detection at 80 FPS |
| SAGM | 0.105 | 0.749 | 0.858 | Saliency-Aware Geodesic Video Object Segmentation |
| MSTM | 0.095 | 0.749 | 0.816 | Real-Time Salient Object Detection With a Minimum Spanning Tree |
| MBNM | 0.047 | 0.857 | 0.892 | Unsupervised Video Object Segmentation with Motion-based Bilateral Networks |
| FGRN | 0.045 | 0.861 | 0.945 | Flow Guided Recurrent Neural Encoder for Video Salient Object Detection |
| PDB | 0.032 | 0.907 | 0.846 | Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection |
| SSAV | 0.021 | 0.942 | 0.980 | Shifting More Attention to Video Salient Object Detection |
| UFO | 0.011 | 0.953 | 0.987 | A Unified Transformer Framework for Group-based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object Detection |
| RealFlow | 0.010 | 0.962 | 0.966 | Transforming Static Images Using Generative Models for Video Salient Object Detection |
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