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Models/ProPos*

ProPos*

Reported on 8 benchmarks across 1 task · 1 paper · 3 SOTA

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

Computer Vision8 results

Image ClusteringonImagenet-dog-15
ARI· 2021-11-23
0.675
best: 0.879 (MAE-CT (best))
SOTA
Learning Representation for Clustering via Prototype Scattering and Positive Sampling arXiv:2111.11821
Image ClusteringonImagenet-dog-15
Accuracy· 2021-11-23
0.775
best: 0.943 (MAE-CT (best))
SOTA
Learning Representation for Clustering via Prototype Scattering and Positive Sampling arXiv:2111.11821
Image ClusteringonImagenet-dog-15
NMI· 2021-11-23
0.737
best: 0.904 (MAE-CT (best))
SOTA
Learning Representation for Clustering via Prototype Scattering and Positive Sampling arXiv:2111.11821
Image ClusteringonImageNet-10
ARI· 2021-11-23
0.918
best: 0.935 (DPAC)
Learning Representation for Clustering via Prototype Scattering and Positive Sampling arXiv:2111.11821
Image ClusteringonImageNet-10
Accuracy· 2021-11-23
0.962
best: 0.992 (TAC)
Learning Representation for Clustering via Prototype Scattering and Positive Sampling arXiv:2111.11821
Image ClusteringonImageNet-10
Image Size· 2021-11-23
224
Learning Representation for Clustering via Prototype Scattering and Positive Sampling arXiv:2111.11821
Image ClusteringonImageNet-10
NMI· 2021-11-23
0.908
best: 0.985 (TAC)
Learning Representation for Clustering via Prototype Scattering and Positive Sampling arXiv:2111.11821
Image ClusteringonImagenet-dog-15
Image Size· 2021-11-23
224
Learning Representation for Clustering via Prototype Scattering and Positive Sampling arXiv:2111.11821