Contrastive Learning with Stronger Augmentations
Author:
Affiliation:
1. Department of Computer Science, Purdue University, West Lafayette, USA
2. Futurewei Seattle Cloud Lab, Seattle, WA, USA
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software
Link
http://xplorestaging.ieee.org/ielx7/34/4359286/09873966.pdf?arnumber=9873966
Reference67 articles.
1. Local Aggregation for Unsupervised Learning of Visual Embeddings
2. Faster AutoAugment: Learning Augmentation Strategies Using Backpropagation
3. Learning representations by maximizing mutual information across views;bachman;Proc Int Conf Neural Inf Process,2019
4. CaCo: Both positive and negative samples are directly learnable via cooperative-adversarial contrastive learning;wang,2022
5. Data-efficient image recognition with contrastive predictive coding;hénaff,2019
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