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SotA/Computer Vision/Image Clustering/Imagenet-dog-15

Image Clustering on Imagenet-dog-15

Metric: NMI (higher is better)

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#Model↕NMI▼Extra DataPaperDate↕Code
1MAE-CT (best)0.904YesContrastive Tuning: A Little Help to Make Masked...2023-04-20Code
2MAE-CT (mean)0.882YesContrastive Tuning: A Little Help to Make Masked...2023-04-20Code
3PRO-DSC0.812YesExploring a Principled Framework for Deep Subspa...2025-03-21Code
4ProPos*0.737NoLearning Representation for Clustering via Proto...2021-11-23Code
5ProPos0.692NoLearning Representation for Clustering via Proto...2021-11-23Code
6DPAC0.667NoDeep Online Probability Aggregation Clustering2024-07-07Code
7ConCURL0.63NoRepresentation Learning for Clustering via Build...2021-05-04Code
8SPICE0.627NoSPICE: Semantic Pseudo-labeling for Image Cluste...2021-03-17Code
9TCL0.623NoTwin Contrastive Learning for Online Clustering2022-10-21Code
10IDFD0.546NoClustering-friendly Representation Learning via ...2021-05-31Code
11C30.448NoC3: Cross-instance guided Contrastive Clustering2022-11-14Code
12CC0.445NoContrastive Clustering2020-09-21Code
13MiCE0.423NoMiCE: Mixture of Contrastive Experts for Unsuper...2021-05-05Code
14CoHiClust0.411NoContrastive Hierarchical Clustering2023-03-03Code
15DCCM0.321NoDeep Comprehensive Correlation Mining for Image ...2019-04-15Code
16DAC0.219No--Code
17DEC0.122NoUnsupervised Deep Embedding for Clustering Analy...2015-11-19Code
18GAN0.121NoUnsupervised Representation Learning with Deep C...2015-11-19Code
19VAE0.107NoAuto-Encoding Variational Bayes2013-12-20Code
20JULE0.054NoJoint Unsupervised Learning of Deep Representati...2016-04-13Code