Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning

• URL: http://arxiv.org/abs/2108.01775v1
• Date: Tue, 3 Aug 2021 22:19:55 GMT
• Title: Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning
• Authors: Victor G. Turrisi da Costa and Enrico Fini and Moin Nabi and Nicu Sebe and Elisa Ricci
• Abstract summary: solo-learn is a library of self-supervised methods for visual representation learning. Implemented in Python, using Pytorch and Pytorch lightning, the library fits both research and industry needs.
• Score: 83.02597612195966
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper presents solo-learn, a library of self-supervised methods for visual representation learning. Implemented in Python, using Pytorch and Pytorch lightning, the library fits both research and industry needs by featuring distributed training pipelines with mixed-precision, faster data loading via Nvidia DALI, online linear evaluation for better prototyping, and many additional training tricks. Our goal is to provide an easy-to-use library comprising a large amount of Self-supervised Learning (SSL) methods, that can be easily extended and fine-tuned by the community. solo-learn opens up avenues for exploiting large-budget SSL solutions on inexpensive smaller infrastructures and seeks to democratize SSL by making it accessible to all. The source code is available at https://github.com/vturrisi/solo-learn.

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