Methods › General › Self-Supervised Learning › DeepCluster

DeepCluster

10 papers tagged archive 2025-07-28

Introduced by Mathilde Caron et al. in Deep Clustering for Unsupervised Learning of Visual Features

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

DeepCluster is a self-supervision approach for learning image representations. DeepCluster iteratively groups the features with a standard clustering algorithm, k-means, and uses the subsequent assignments as supervision to update the weights of the network

PaperSource

Papers archive 2025-07-28

10 shown of 10, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Clustering5
Self-Supervised Learning4
Data Augmentation2
Graph Learning2
Representation Learning2
image-classification2
Anomaly Detection1
Change Detection1
Deep Clustering1
Face Clustering1
Federated Learning1
Graph Embedding1
Image Classification1
Image Clustering1
Self-Supervised Image Classification1
Semantic Segmentation1
Speech Recognition1
Unsupervised Semantic Segmentation1
imbalanced classification1
speech-recognition1

Usage over time archive 2025-07-28

Papers per year tagged with DeepCluster: 2018 to 2024, peak 2 2 0 2018: 1 paper 2018 2019: 2 papers 2019 2020: 0 papers 2020 2021: 2 papers 2021 2022: 2 papers 2022 2023: 2 papers 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (10 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Self-Supervised Learning

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