Unsupervised Semantic Segmentation On Coco 7
Metrics
Accuracy
mIoU
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy | mIoU |
|---|---|---|
| Model 1 | 63.2 | 26.7 |
| invariant-information-distillation-for | 21.8 | - |
| expand-and-quantize-unsupervised-semantic | 53.8 | 25.8 |
| unsupervised-semantic-segmentation-by-2 | 56.9 | 28.2 |
| causal-unsupervised-semantic-segmentation | 74.9 | 41.9 |
| picie-unsupervised-semantic-segmentation | 49.99 | 14.36 |
| unsupervised-image-semantic-segmentation | 55.7 | - |
| self-supervised-visual-representation-2 | 42.36 | - |
| fully-self-supervised-learning-for-semantic | 40.38 | 15.69 |
| boosting-unsupervised-semantic-segmentation | 57.8 | 25.1 |
| picie-unsupervised-semantic-segmentation | 48.1 | - |
| unsupervised-universal-image-segmentation | 63.9 | 30.2 |
| expand-and-quantize-unsupervised-semantic | 53.8 | 25.8 |
| rethinking-alignment-and-uniformity-in | 52.0 | - |
| croc-cross-view-online-clustering-for-dense | - | 21.9 |
| leveraging-hidden-positives-for-unsupervised | 57.2 | 24.6 |
| causal-unsupervised-semantic-segmentation | 78.0 | 45.3 |
| unsupervised-semantic-segmentation-by-2 | - | 24.5 |
| boosting-unsupervised-semantic-segmentation | 57.9 | 29.7 |
| vice-self-supervised-visual-concept | 64.8 | 21.77 |
| dynaseg-a-deep-dynamic-fusion-method-for | 81.1 | 54.1 |
| eagle-eigen-aggregation-learning-for-object | 64.2 | 27.2 |