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Models/DEC

DEC

Reported on 15 benchmarks across 2 tasks · 1 paper · 10 SOTA

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

Computer Vision15 results

Image ClusteringonImageNet-10
Accuracy· 2015-11-19
0.381
best: 0.992 (TAC)
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonImageNet-10
NMI· 2015-11-19
0.282
best: 0.985 (TAC)
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonCIFAR-100
Accuracy· uses extra data· 2015-11-19
0.185
best: 0.898 (TURTLE (CLIP + DINOv2))
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonCIFAR-100
NMI· uses extra data· 2015-11-19
0.136
best: 0.915 (TURTLE (CLIP + DINOv2))
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonSTL-10
Accuracy· uses extra data· 2015-11-19
0.359
best: 0.997 (TURTLE (CLIP + DINOv2))
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonSTL-10
NMI· uses extra data· 2015-11-19
0.276
best: 0.993 (TURTLE (CLIP + DINOv2))
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonImagenet-dog-15
Accuracy· 2015-11-19
0.195
best: 0.943 (MAE-CT (best))
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonImagenet-dog-15
NMI· 2015-11-19
0.122
best: 0.904 (MAE-CT (best))
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClassificationonSVHN
# of clusters (k)· uses extra data· 2015-11-19
10
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClassificationonSVHN
Acc· uses extra data· 2015-11-19
11.9
best: 76.8 (ACOL-GAR)
SOTA
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonCIFAR-10
ARI· uses extra data· 2015-11-19
0.161
best: 0.989 (TURTLE (CLIP + DINOv2))
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonCIFAR-10
Accuracy· uses extra data· 2015-11-19
0.301
best: 0.995 (TURTLE (CLIP + DINOv2))
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonCIFAR-10
NMI· uses extra data· 2015-11-19
0.25
best: 0.985 (TURTLE (CLIP + DINOv2))
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonTiny-ImageNet
Accuracy· 2015-11-19
0.037
best: 0.698 (PRO-DSC)
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335
Image ClusteringonTiny-ImageNet
NMI· 2015-11-19
0.115
best: 0.8178 (ITAE)
Unsupervised Deep Embedding for Clustering Analysis arXiv:1511.06335