Self-Supervised Learning for OOD Detection

A Simplified Pytorch implementation of Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty(NeurIPS 2019)

The code supports only Multi-class OOD Detection experiment(in-dist: CIFAR-10, Out-of-dist: CIFAR-100/SVHN)

• Command

  • RotNet-OOD

    python test.py --method=rot --ood_dataset=cifar100

  • baseline

    python test.py --method=msp --ood_dataset=svhn

• Reference

  • full code(by authors): https://github.com/hendrycks/ss-ood
  • Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty(NeurIPS 2019): https://arxiv.org/abs/1906.12340
  • A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks(ICLR 2017): https://arxiv.org/abs/1610.02136