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Unofficial PyTorch Implementation of Unsupervised Data Augmentation.

UDA : Unsupervised Data Augmentation

Unofficial PyTorch Implementation of Unsupervised Data Augmentation.

  • Experiments on Text Dataset need to be done. Any Pull-Requests would be appreciated.
  • Augmentation policies for SVHN, Imagenet using AutoAugment are not available publicly. We use policies from Fast AutoAugment.

Most of codes are from Fast AutoAugment.

Introduction

todo.

Run

$ python train.py -c confs/wresnet28x2.yaml --unsupervised

Experiments

Cifar10 (Reduced, 4k dataset)

Reproduce Paper's Result

WResNet 28x2 Paper Our Converged(Top1 Err) Our Best(Top1 Err)
Supervised 20.26 21.30
AutoAugment 14.1* 15.4 13.4
UDA 5.27 6.58 6.27

SVHN

todo.

ImageNet

todo.

References

  • Unsupervised Data Augmentation : https://arxiv.org/abs/1904.12848v1
    • Official Tensorflow Implementation : https://github.com/google-research/uda
  • Fast AutoAugment : https://github.com/kakaobrain/fast-autoaugment