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Models/TEMI CLIP ViT-L (openai)

TEMI CLIP ViT-L (openai)

Reported on 15 benchmarks across 1 task · 1 paper · 15 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-100 (TEMI Split)
ACCURACY· uses extra data· 2023-03-31
0.8343
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-100 (TEMI Split)
ARI· uses extra data· 2023-03-31
0.7581
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-100 (TEMI Split)
NMI· uses extra data· 2023-03-31
0.9006
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonCIFAR-10
ARI· uses extra data· 2023-03-31
0.932
best: 0.989 (TURTLE (CLIP + DINOv2))
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonCIFAR-10
Accuracy· uses extra data· 2023-03-31
0.969
best: 0.995 (TURTLE (CLIP + DINOv2))
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonCIFAR-10
NMI· uses extra data· 2023-03-31
0.926
best: 0.985 (TURTLE (CLIP + DINOv2))
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonCIFAR-100
ARI· uses extra data· 2023-03-31
0.612
best: 0.834 (TURTLE (CLIP + DINOv2))
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonCIFAR-100
Accuracy· uses extra data· 2023-03-31
0.737
best: 0.898 (TURTLE (CLIP + DINOv2))
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonCIFAR-100
NMI· uses extra data· 2023-03-31
0.799
best: 0.915 (TURTLE (CLIP + DINOv2))
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-200
ACCURACY· uses extra data· 2023-03-31
0.7776
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-200
ARI· uses extra data· 2023-03-31
0.6941
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-200
NMI· uses extra data· 2023-03-31
0.8839
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-50 (TEMI Split)
ACCURACY· uses extra data· 2023-03-31
0.8827
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-50 (TEMI Split)
ARI· uses extra data· 2023-03-31
0.8272
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-50 (TEMI Split)
NMI· uses extra data· 2023-03-31
0.9232
SOTA
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896