DOS

An official PyTorch implementation of the ICLR 2024 paper
"DOS: Diverse Outlier Sampling for Out-of-Distribution Detection"

   

Get Started • Citation

Get Started

Overview

This repository is an official PyTorch implementation of the ICLR 2024 paper 'DOS: Diverse Outlier Sampling for Out-of-Distribution Detection'. The illustration of our algorithm is shown as below:

Requirements

pip install -r requirements.txt

Training

python train_diverse.py

Evaluation

OODs="svhn lsunc dtd places365_10k tinc lsunr tinr isun"
python detect.py --id cifar100 --ood $OODs --score abs --pretrain /path/to/trained/classifier

Results

Citation

If you find our repository useful for your research, please consider citing our paper:

@inproceedings{jiang2024dos,
  title={{DOS}: Diverse Outlier Sampling for Out-of-Distribution Detection},
  author={Wenyu Jiang and Hao Cheng and MingCai Chen and Chongjun Wang and Hongxin Wei},
  booktitle={The Twelfth International Conference on Learning Representations},
  year={2024},
  url={https://openreview.net/forum?id=iriEqxFB4y}
}