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Models/PriMaPs+STEGO (DINO ViT-B/8)

PriMaPs+STEGO (DINO ViT-B/8)

Reported on 6 benchmarks across 3 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical2 results

Semantic SegmentationonCOCO-Stuff-27
Clustering [Accuracy]· 2024-04-25
57.9
best: 81.1 (DynaSeg - FSF (ResNet-18 FPN))
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals arXiv:2404.16818
Semantic SegmentationonCOCO-Stuff-27
Clustering [mIoU]· 2024-04-25
29.7
best: 54.1 (DynaSeg - FSF (ResNet-18 FPN))
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals arXiv:2404.16818

Computer Vision2 results

Unsupervised Semantic SegmentationonCOCO-Stuff-27
Clustering [Accuracy]· 2024-04-25
57.9
best: 81.1 (DynaSeg - FSF (ResNet-18 FPN))
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals arXiv:2404.16818
Unsupervised Semantic SegmentationonCOCO-Stuff-27
Clustering [mIoU]· 2024-04-25
29.7
best: 54.1 (DynaSeg - FSF (ResNet-18 FPN))
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals arXiv:2404.16818

Audio2 results

10-shot image generationonCOCO-Stuff-27
Clustering [Accuracy]· 2024-04-25
57.9
best: 81.1 (DynaSeg - FSF (ResNet-18 FPN))
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals arXiv:2404.16818
10-shot image generationonCOCO-Stuff-27
Clustering [mIoU]· 2024-04-25
29.7
best: 54.1 (DynaSeg - FSF (ResNet-18 FPN))
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals arXiv:2404.16818