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08/08/2023
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
Synthetic image datasets offer unmatched advantages for designing and ev...
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07/31/2023
Predicting masked tokens in stochastic locations improves masked image modeling
Self-supervised learning is a promising paradigm in deep learning that e...
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04/26/2023
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning
Self-supervised learning (SSL) algorithms can produce useful image repre...
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04/25/2023
Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations
Joint-embedding based learning (e.g., SimCLR, MoCo, DINO) and reconstruc...
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04/24/2023
A Cookbook of Self-Supervised Learning
Self-supervised learning, dubbed the dark matter of intelligence, is a p...
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04/11/2023
A surprisingly simple technique to control the pretraining bias for better transfer: Expand or Narrow your representation
Self-Supervised Learning (SSL) models rely on a pretext task to learn re...
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03/03/2023
Towards Democratizing Joint-Embedding Self-Supervised Learning
Joint Embedding Self-Supervised Learning (JE-SSL) has seen rapid develop...
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10/13/2022
The Hidden Uniform Cluster Prior in Self-Supervised Learning
A successful paradigm in representation learning is to perform self-supe...
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06/27/2022
Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head
One unexpected technique that emerged in recent years consists in traini...
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04/14/2022
Masked Siamese Networks for Label-Efficient Learning
We propose Masked Siamese Networks (MSN), a self-supervised learning fra...
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12/16/2021
High Fidelity Visualization of What Your Self-Supervised Representation Knows About
Discovering what is learned by neural networks remains a challenge. In s...
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03/20/2017