# Oquab 2023: DINOv2: Learning Robust Visual Features without Supervision

> Maxime Oquab, Timothée Darcet, Théo Moutakanni et al., 2023. 1 records on Mysteries Department cite it. The emerging-methods survey proposes it, with…

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[Sources](https://mysteriesdept.com/sources)[Voynich Manuscript](https://mysteriesdept.com/mysteries/voynich-manuscript)Oquab 2023

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# DINOv2: Learning Robust Visual Features without Supervision

Maxime Oquab, Timothée Darcet, Théo Moutakanni et al., 2023. _arXiv_.

Introduces DINOv2, a family of vision models trained without labels to produce general-purpose image features.

**Voynich Manuscript** PreprintChecked against the original0

## What it's used for here

The emerging-methods survey proposes it, with Segment Anything and CLIP, for unsupervised clustering and segmentation of glyphs.

## Cited by on this site 1 record

[1 methods surveys]

Mathematics

SRC

## Cite it

```
Oquab, M., Darcet, T., Moutakanni, T., Vo, H., Szafraniec, M., Khalidov, V., Fernandez, P., Haziza, D., Massa, F., El-Nouby, A., Assran, M., Ballas, N., Galuba, W., Howes, R., Huang, P. Y., Li, S. W., Misra, I., Rabbat, M., Sharma, V., Synnaeve, G., Xu, H., Jegou, H., Mairal, J., Labatut, P., Joulin, A., & Bojanowski, P. (2023). DINOv2: Learning Robust Visual Features without Supervision. arXiv. https://arxiv.org/abs/2304.07193
```

[Read it free at arxiv.org](https://arxiv.org/abs/2304.07193)

Key

**SRC** 0D8MSCA42P1S

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Preprint

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arXiv-nonexclusive

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