Search Results for author: Geoff French

Found 4 papers, 2 papers with code

Colour augmentation for improved semi-supervised semantic segmentation

no code implementations9 Oct 2021 Geoff French, Michal Mackiewicz

Consistency regularization describes a class of approaches that have yielded state-of-the-art results for semi-supervised classification.

Classification Self-Supervised Learning +1

Milking CowMask for Semi-Supervised Image Classification

2 code implementations26 Mar 2020 Geoff French, Avital Oliver, Tim Salimans

Using it to provide perturbations for semi-supervised consistency regularization, we achieve a state-of-the-art result on ImageNet with 10% labeled data, with a top-5 error of 8. 76% and top-1 error of 26. 06%.

Classification General Classification +1

Semi-supervised semantic segmentation needs strong, high-dimensional perturbations

no code implementations25 Sep 2019 Geoff French, Timo Aila, Samuli Laine, Michal Mackiewicz, Graham Finlayson

Consistency regularization describes a class of approaches that have yielded ground breaking results in semi-supervised classification problems.

Semi-Supervised Semantic Segmentation

Semi-supervised semantic segmentation needs strong, varied perturbations

3 code implementations5 Jun 2019 Geoff French, Samuli Laine, Timo Aila, Michal Mackiewicz, Graham Finlayson

We analyze the problem of semantic segmentation and find that its' distribution does not exhibit low density regions separating classes and offer this as an explanation for why semi-supervised segmentation is a challenging problem, with only a few reports of success.

General Classification Semi-Supervised Semantic Segmentation

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