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Models/SPICE

SPICE

Reported on 9 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 Vision9 results

Image ClusteringonImageNet-10
ARI· 2021-03-17
0.933
best: 0.935 (DPAC)
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonImageNet-10
Accuracy· 2021-03-17
0.969
best: 0.992 (TAC)
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonImageNet-10
NMI· 2021-03-17
0.927
best: 0.985 (TAC)
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonTiny-ImageNet
ARI· 2021-03-17
0.161
best: 0.5227 (ITAE)
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonTiny-ImageNet
Accuracy· 2021-03-17
0.305
best: 0.698 (PRO-DSC)
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonImagenet-dog-15
ARI· 2021-03-17
0.526
best: 0.879 (MAE-CT (best))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonImagenet-dog-15
Accuracy· 2021-03-17
0.675
best: 0.943 (MAE-CT (best))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonImagenet-dog-15
NMI· 2021-03-17
0.627
best: 0.904 (MAE-CT (best))
SOTA
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382
Image ClusteringonTiny-ImageNet
NMI· 2021-03-17
0.449
best: 0.8178 (ITAE)
SPICE: Semantic Pseudo-labeling for Image Clustering arXiv:2103.09382