most citedDivide and Contrast: Self-supervised Learning from Uncurated Data

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

cs.CV2021★ 1 cited

Divide and Contrast: Self-supervised Learning from Uncurated Data

Yonglong Tian, Olivier J. Henaff, Aaron van den Oord

Self-supervised learning holds promise in leveraging large amounts of unlabeled data, however much of its progress has thus far been limited to highly curated pre-training data suc…

cs.CV2019

Data-Efficient Image Recognition with Contrastive Predictive Coding

Olivier J. Hénaff, Aravind Srinivas, Jeffrey De Fauw +4

Human observers can learn to recognize new categories of images from a handful of examples, yet doing so with artificial ones remains an open challenge. We hypothesize that data-ef…