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Cyprien de Masson d'Autume
34 lines
955 B
Markdown
34 lines
955 B
Markdown
# Unrestricted Adversarial Challenge
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This is a submission for the unrestricted adversarial challenge: Phase I. The
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entry is uses a pretrained ImageNet model with Local Linearity Regularizer, then
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adversarially trained using birds-or-bicycles dataset (train and extras) as
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provided by the challenge.
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> Tom B. Brown et al
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*Unrestricted Adversarial Examples*. [\[arXiv\]](https://arxiv.org/pdf/1809.08352).
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> Chongli Qin et al
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*Adversarial Robustness through Local Linearization*. NEURIPS 2019. [\[arXiv\]](https://arxiv.org/abs/1907.02610)
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## Contents
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The code contains:
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- a main file (`main.py`) for our submission.
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## Running
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Install requirements please follow instructions on
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[Unrestricted Adversarial Challenge.](https://github.com/google/unrestricted-adversarial-examples/blob/master/warmup.md)
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You can do this by running:
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./unrestricted_advx/install_dependencies.sh
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You can run the main script by:
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./unrestricted_advx/run.sh
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