Image Clustering

104 papers with code • 33 benchmarks • 21 datasets

Models that partition the dataset into semantically meaningful clusters without having access to the ground truth labels.

Image credit: ImageNet clustering results of SCAN: Learning to Classify Images without Labels (ECCV 2020)

Libraries

Use these libraries to find Image Clustering models and implementations

MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations

ml-jku/MIM-Refiner 15 Feb 2024

The motivation behind MIM-Refiner is rooted in the insight that optimal representations within MIM models generally reside in intermediate layers.

21
15 Feb 2024

The VampPrior Mixture Model

astirn/vampprior-mixture-model 6 Feb 2024

Current clustering priors for deep latent variable models (DLVMs) require defining the number of clusters a-priori and are susceptible to poor initializations.

1
06 Feb 2024

Text-Guided Image Clustering

andst/text_guided_cl 5 Feb 2024

We, therefore, propose Text-Guided Image Clustering, i. e., generating text using image captioning and visual question-answering (VQA) models and subsequently clustering the generated text.

4
05 Feb 2024

Learning Representations for Clustering via Partial Information Discrimination and Cross-Level Interaction

regan-zhang/pici 24 Jan 2024

In this paper, we present a novel deep image clustering approach termed PICI, which enforces the partial information discrimination and the cross-level interaction in a joint learning framework.

0
24 Jan 2024

Deep Structure and Attention Aware Subspace Clustering

cs-whh/dsasc 25 Dec 2023

However, previous deep clustering methods, especially image clustering, focus on the features of the data itself and ignore the relationship between the data, which is crucial for clustering.

3
25 Dec 2023

Superpixel-based and Spatially-regularized Diffusion Learning for Unsupervised Hyperspectral Image Clustering

ckn3/s2dl 24 Dec 2023

However, the high dimensionality, presence of noise and outliers, and the need for precise labels of HSIs present significant challenges to HSIs analysis, motivating the development of performant HSI clustering algorithms.

5
24 Dec 2023

Stable Cluster Discrimination for Deep Clustering

idstcv/secu ICCV 2023

Meanwhile, one-stage methods are developed mainly for representation learning rather than clustering, where various constraints for cluster assignments are designed to avoid collapsing explicitly.

10
24 Nov 2023

Image Clustering Conditioned on Text Criteria

sehyunkwon/ictc 27 Oct 2023

Classical clustering methods do not provide users with direct control of the clustering results, and the clustering results may not be consistent with the relevant criterion that a user has in mind.

61
27 Oct 2023

The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning

mlbio-epfl/hume NeurIPS 2023

Despite its simplicity, HUME outperforms a supervised linear classifier on top of self-supervised representations on the STL-10 dataset by a large margin and achieves comparable performance on the CIFAR-10 dataset.

11
21 Sep 2023

Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models

leslietrue/cpp 8 Jun 2023

In this paper, we propose a novel image clustering pipeline that leverages the powerful feature representation of large pre-trained models such as CLIP and cluster images effectively and efficiently at scale.

20
08 Jun 2023