Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/TEMI MSN ViT-L

TEMI MSN ViT-L

Reported on 8 benchmarks across 1 task · 1 paper

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

Computer Vision8 results

Image ClusteringonImageNet-100 (TEMI Split)
ACCURACY· uses extra data· 2023-03-31
0.8286
best: 0.8343 (TEMI CLIP ViT-L (openai))
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
0.7408
best: 0.7581 (TEMI CLIP ViT-L (openai))
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
0.8853
best: 0.9006 (TEMI CLIP ViT-L (openai))
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-200
ARI· uses extra data· 2023-03-31
0.667
best: 0.6941 (TEMI CLIP ViT-L (openai))
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896
Image ClusteringonImageNet-200
NMI· uses extra data· 2023-03-31
0.8665
best: 0.8839 (TEMI CLIP ViT-L (openai))
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
0.8487
best: 0.8827 (TEMI CLIP ViT-L (openai))
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
0.7646
best: 0.8272 (TEMI CLIP ViT-L (openai))
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
0.8814
best: 0.9232 (TEMI CLIP ViT-L (openai))
Exploring the Limits of Deep Image Clustering using Pretrained Models arXiv:2303.17896