Awesome
Out-of-Distribution Detection Using Union of 1-Dimensional Subspaces
Implementation of the out-of-distribution detection method proposed in:
A. Zaeemzadeh, N. Bisagno, Z. Sambugaro, N. Conci, N. Rahnavard, and M. Shah: Out-of-Distribution Detection Using Union of 1-Dimensional Subspaces. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. link
- For experiments on UCF101 video dataset see here.
Running the code
Tested on:
- Python 3.9
- cuda 11.2
- torch 1.8.1
- torchvision 0.9.1
- numpy 1.20.1
- sklearn 0.24.1
Downloading Out-of-Distribtion Datasets
See this repo.
Sample Script
See main.sh
.
Citing this work
If you use this work in your research, please use the following BibTeX entry.
@inproceedings{zaeemzadeh2021ood,
title={Out-of-Distribution Detection Using Union of 1-Dimensional Subspaces},
year = {2021},
booktitle = {Computer Vision and Pattern Recognition, 2021. CVPR 2021. IEEE Conference on},
author={Zaeemzadeh, Alireza and Bisagno, Niccol{\`o} and Sambugaro, Zeno and Conci, Nicola and Rahnavard, Nazanin and Shah, Mubarak}
}