Instance Segmentation On Cityscapes Val
Metrics
mask AP
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | mask AP |
|---|---|
| masked-attention-mask-transformer-for | 43.7 |
| oneformer-one-transformer-to-rule-universal | 48.7 |
| masked-attention-mask-transformer-for | 41.8 |
| geometry-aware-instance-segmentation-with | 37.1 |
| dilated-neighborhood-attention-transformer | 45.1 |
| masked-attention-mask-transformer-for | 38.5 |
| masked-attention-mask-transformer-for | 42 |
| a-simple-framework-for-open-vocabulary | 49.3 |
| recurrent-contour-based-instance-segmentation | 40.2 |
| masked-attention-mask-transformer-for | 39.7 |
| autofocusformer-image-segmentation-off-the | 46.2 |
| oneformer-one-transformer-to-rule-universal | 45.6 |
| autofocusformer-image-segmentation-off-the | 44.0 |
| oneformer-one-transformer-to-rule-universal | 45.6 |
| pointrend-image-segmentation-as-rendering | 35.8 |
| masked-attention-mask-transformer-for | 37.4 |