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Models/SR-K-means

SR-K-means

Reported on 11 benchmarks across 1 task · 1 paper · 4 SOTA

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

Computer Vision11 results

Image ClusteringonCMU-PIE
Accuracy· 2018-10-09
0.902
SOTA
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonUSPS
Accuracy· 2018-10-09
0.974
best: 0.984 (SPC)
SOTA
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonUSPS
NMI· 2018-10-09
0.936
best: 0.954 (SPC)
SOTA
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonMNIST-test
Accuracy· 2018-10-09
0.863
best: 0.987 (DynAE)
SOTA
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonCMU-PIE
NMI· 2018-10-09
0.945
best: 1 (JULE-RC)
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonMNIST-full
NMI· 2018-10-09
0.913
best: 0.975 (SPC)
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonFRGC
Accuracy· 2018-10-09
0.413
best: 0.432 (DEPICT)
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonFRGC
NMI· 2018-10-09
0.487
best: 0.583 (DEPICT)
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonYouTube Faces DB
Accuracy· 2018-10-09
0.605
best: 0.611 (DEPICT)
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonYouTube Faces DB
NMI· 2018-10-09
0.806
best: 0.848 (JULE-RC)
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246
Image ClusteringonMNIST-test
NMI· 2018-10-09
0.873
best: 0.963 (DynAE)
Deep clustering: On the link between discriminative models and K-means arXiv:1810.04246