Unsupervised Video Object Segmentation On 5
Métriques
F-measure (Decay)
F-measure (Mean)
F-measure (Recall)
Ju0026F
Jaccard (Decay)
Jaccard (Mean)
Jaccard (Recall)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | F-measure (Decay) | F-measure (Mean) | F-measure (Recall) | Ju0026F | Jaccard (Decay) | Jaccard (Mean) | Jaccard (Recall) | Paper Title | Repository |
|---|---|---|---|---|---|---|---|---|---|
| UnOVSOT | 6.6 | 62.0 | 66.6 | 58.0 | 3.5 | 54.0 | 62.9 | UnOVOST: Unsupervised Offline Video Object Segmentation and Tracking | |
| AGS | 2.6 | 49.0 | 51.5 | 45.6 | 2.6 | 42.1 | 48.5 | Learning Unsupervised Video Object Segmentation Through Visual Attention | - |
| PDB | 3.7 | 43.0 | 44.6 | 40.4 | 4.0 | 37.7 | 42.6 | Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection | - |
| DEVA (EntitySeg) | - | - | - | 62.1 | - | - | - | Tracking Anything with Decoupled Video Segmentation | |
| RVOS | 1.8 | 27.3 | 24.8 | 22.5 | 1.6 | 17.7 | 16.2 | RVOS: End-to-End Recurrent Network for Video Object Segmentation | |
| MuG-W | -1.7 | 44.5 | 46.6 | 41.7 | -2.7 | 38.9 | 44.3 | Learning Video Object Segmentation from Unlabeled Videos |
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