Local Aggregation for Unsupervised Learning of Visual Embeddings

1 code implementation • ICCV 2019 • Chengxu Zhuang, Alex Lin Zhai, Daniel Yamins

Unsupervised approaches to learning in neural networks are of substantial interest for furthering artificial intelligence, both because they would enable the training of networks without the need for large numbers of expensive annotations, and because they would be better models of the kind of general-purpose learning deployed by humans.

Clustering Contrastive Learning +6