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Models/EQUSS (ViT-S)

EQUSS (ViT-S)

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]· 2023-12-12
53.8
best: 81.1 (DynaSeg - FSF (ResNet-18 FPN))
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization arXiv:2312.07342
Semantic SegmentationonCOCO-Stuff-27
Clustering [mIoU]· 2023-12-12
25.8
best: 54.1 (DynaSeg - FSF (ResNet-18 FPN))
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization arXiv:2312.07342

Computer Vision2 results

Unsupervised Semantic SegmentationonCOCO-Stuff-27
Clustering [Accuracy]· 2023-12-12
53.8
best: 81.1 (DynaSeg - FSF (ResNet-18 FPN))
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization arXiv:2312.07342
Unsupervised Semantic SegmentationonCOCO-Stuff-27
Clustering [mIoU]· 2023-12-12
25.8
best: 54.1 (DynaSeg - FSF (ResNet-18 FPN))
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization arXiv:2312.07342

Audio2 results

10-shot image generationonCOCO-Stuff-27
Clustering [Accuracy]· 2023-12-12
53.8
best: 81.1 (DynaSeg - FSF (ResNet-18 FPN))
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization arXiv:2312.07342
10-shot image generationonCOCO-Stuff-27
Clustering [mIoU]· 2023-12-12
25.8
best: 54.1 (DynaSeg - FSF (ResNet-18 FPN))
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization arXiv:2312.07342