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EquiMod: An Equivariance Module to Improve Visual Instance Discrimination

Recent self-supervised visual representation methods are closing the gap with supervised learning performance. Most of these successful methods rely on maximizing the similarity between embeddings of related synthetic inputs created through data augmentations.

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Cite this as

Alexandre Devillers, Mathieu Lefort (2024). Dataset: EquiMod: An Equivariance Module to Improve Visual Instance Discrimination. https://doi.org/10.57702/uk06s9hq

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Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Author	Alexandre Devillers
More Authors	Mathieu Lefort
Homepage	https://github.com/ADevillers/