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Models/SPICE*

SPICE*

Reported on 8 benchmarks across 1 task · 1 paper · 8 SOTA

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

Computer Vision8 results

Image ClusteringonCIFAR-10
ARI· 2021-03-17
0.836
best: 0.989 (TURTLE (CLIP + DINOv2))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonCIFAR-10
Accuracy· 2021-03-17
0.918
best: 0.995 (TURTLE (CLIP + DINOv2))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonCIFAR-10
NMI· 2021-03-17
0.85
best: 0.985 (TURTLE (CLIP + DINOv2))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonCIFAR-100
ARI· 2021-03-17
0.422
best: 0.834 (TURTLE (CLIP + DINOv2))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonCIFAR-100
Accuracy· 2021-03-17
0.584
best: 0.898 (TURTLE (CLIP + DINOv2))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonCIFAR-100
NMI· 2021-03-17
0.583
best: 0.915 (TURTLE (CLIP + DINOv2))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonSTL-10
Accuracy· 2021-03-17
0.929
best: 0.997 (TURTLE (CLIP + DINOv2))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonSTL-10
NMI· 2021-03-17
0.86
best: 0.993 (TURTLE (CLIP + DINOv2))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382