Image Clustering On Fashion Mnist
评估指标
Accuracy
NMI
评测结果
各个模型在此基准测试上的表现结果
模型名称 | Accuracy | NMI | Paper Title | Repository |
|---|---|---|---|---|
| DDC | 0.619 | 0.682 | Deep Density-based Image Clustering | |
| DTI-Clustering | 0.612 | 0.637 | Deep Transformation-Invariant Clustering | |
| SNNL-4 | 0.555 | 0.574 | Improving k-Means Clustering Performance with Disentangled Internal Representations | |
| DEN | 0.635 | 0.71 | Interpretable Visualizations with Differentiating Embedding Networks | |
| PSSC | 0.628 | 0.644 | Scattering Transform Based Image Clustering using Projection onto Orthogonal Complement | |
| CoHiClust | 0.65 | - | Contrastive Hierarchical Clustering | |
| SPC | 0.679 | 0.735 | Selective Pseudo-label Clustering | |
| N2D (UMAP) | 0.672 | 0.684 | N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding | |
| DDC-DA | 0.609 | 0.661 | Deep Density-based Image Clustering | |
| GDL | 0.627 | 0.66 | Graph Degree Linkage: Agglomerative Clustering on a Directed Graph | |
| DynAE | 0.591 | 0.642 | Deep Clustering with a Dynamic Autoencoder: From Reconstruction towards Centroids Construction | |
| PRCut (DinoV2) | 0.791 | 0.758 | Deep Clustering via Probabilistic Ratio-Cut Optimization | - |
| VMM | 0.716 | 0.710 | The VampPrior Mixture Model |
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