Deep Clustering for Unsupervised Learning of Visual Features
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The momentum teacher in DINO can be interpreted as a form of Polyak-Ruppert averaging with an exponential decay.
“We propose to interpret the momentum teacher in DINO as a form of Polyak-Ruppert averaging [51, 59] with an exponentially decay.”
From Emerging Properties in Self-Supervised Vision Transformers (2021) · cites this paper as [59]
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“Several variants allow automatic grouping of instances in the form of clustering [2, 7, 8, 21, 29, 35, 61, 65, 69].”
Self-citationBillion-scale similarity search with GPUs
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“An alternative to text-guided pretraining is self-supervised learning (Caron et al., 2018; Chen et al., 2020; He et al., 2022) where features are learned from images alone.”
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“resentations and their cluster assignments [46], and the prediction of the relative positions of image patches [47].”
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- Authors
- Caron, M., Bojanowski, P., Joulin, A., & Douze, M.
- Affiliations
- Meta (United States) (US)
- Corresponding author
- Caron, Mathilde
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 139-156
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2883725317
- Cited by
- 2,674
- References
- 7
- Citations by year
- 2026: 139 · 2025: 276 · 2024: 406 · 2023: 456 · 2022: 489 · 2021: 496 · 2020: 296 · 2019: 107 · 2018: 9
- FWCI
- 68.50
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Clustering Algorithms Research
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Keywords
- deep clustering, unsupervised learning, visual feature learning, K-means clustering, convolutional neural networks, self-supervised learning, ImageNet
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