Unsupervised

Improving Unsupervised Image Clustering With Robust Learning

RUC

This repo is the PyTorch codes for “Improving Unsupervised Image Clustering With Robust Learning (RUC)”

Improving Unsupervised Image Clustering With Robust Learning

Sungwon Park, Sungwon Han, Sundong Kim, Danu Kim, Sungkyu Park, Seunghoon Hong, Meeyoung Cha.

Highlight

  1. RUC is an add-on module to enhance the performance of any off-the-shelf unsupervised learning algorithms. RUC is inspired by robust learning. It first divides clustered data points into clean and noisy set, then refine the clustering results. With RUC, state-of-the-art unsupervised clustering methods; SCAN and TSUC showed showed huge performance improvements. (STL-10 : 86.7%, CIFAR-10 : 90.3%, CIFAR-20 : 54.3%, CIFAR-100 : 36.5 %, ImageNet-50 : 78.5)

main_result
additonal_result

  1. Prediction results of existing unsupervised learning algorithms were overconfident. RUC can make the prediction

     

     

     

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