Instance Segmentation On Occluded Coco
Metrics
Mean Recall
Results
Performance results of various models on this benchmark
Model Name | Mean Recall | Paper Title | Repository |
|---|---|---|---|
| Swin-S + Mask R-CNN | 61.14 | Swin Transformer: Hierarchical Vision Transformer using Shifted Windows | |
| Swin-T + Mask R-CNN | 58.81 | Swin Transformer: Hierarchical Vision Transformer using Shifted Windows | |
| Swin-T + Mask R-CNN (tri-layer plugin) | 62.00 | A Tri-Layer Plugin to Improve Occluded Detection | |
| Swin-B + Cascade Mask R-CNN | 62.90 | Swin Transformer: Hierarchical Vision Transformer using Shifted Windows | |
| Swin-S + Mask R-CNN (tri-layer plugin) | 62.58 | A Tri-Layer Plugin to Improve Occluded Detection | |
| Swin-B + Cascade Mask R-CNN (tri-layer modelling) | 63.64 | A Tri-Layer Plugin to Improve Occluded Detection |
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