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Models/PRO-DSC

PRO-DSC

Reported on 12 benchmarks across 2 tasks · 1 paper · 2 SOTA

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

Computer Vision12 results

Image ClusteringonTiny-ImageNet
Accuracy· uses extra data· 2025-03-21
0.698
SOTA
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClassificationonCIFAR-20
NMI· uses extra data· 2025-03-21
73.2
SOTA
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClusteringonCIFAR-10
Accuracy· uses extra data· 2025-03-21
0.972
best: 0.995 (TURTLE (CLIP + DINOv2))
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClusteringonCIFAR-10
NMI· uses extra data· 2025-03-21
0.928
best: 0.985 (TURTLE (CLIP + DINOv2))
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClusteringonTiny-ImageNet
NMI· uses extra data· 2025-03-21
0.805
best: 0.8178 (ITAE)
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClusteringonCIFAR-100
Accuracy· uses extra data· 2025-03-21
0.773
best: 0.898 (TURTLE (CLIP + DINOv2))
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClusteringonCIFAR-100
NMI· uses extra data· 2025-03-21
0.824
best: 0.915 (TURTLE (CLIP + DINOv2))
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClusteringonImageNet
Accuracy· 2025-03-21
65
best: 72.9 (TURTLE (CLIP + DINOv2))
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClusteringonImageNet
NMI· 2025-03-21
83.4
best: 88.2 (TURTLE (CLIP + DINOv2))
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClusteringonImagenet-dog-15
Accuracy· uses extra data· 2025-03-21
0.84
best: 0.943 (MAE-CT (best))
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClusteringonImagenet-dog-15
NMI· uses extra data· 2025-03-21
0.812
best: 0.904 (MAE-CT (best))
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288
Image ClassificationonCIFAR-20
Accuracy· uses extra data· 2025-03-21
71.6
best: 73.2 (MV-MR)
Exploring a Principled Framework for Deep Subspace Clustering arXiv:2503.17288