Code to accompany [Detecting semantic anomalies, AAAI 2020] (https://arxiv.org/abs/1908.04388).
The rotation folder contains code for the rotation experiments, and the cpc folder for CPC.
The dataloaders for the Imagenet subsets are based off of a lab-internal format of ILSVRC2012, so you'd have to swap out my Fuel-based dataloader for yours.
Requirements are Python 2.7, TensorFlow v1.13.1 (I've used the wheel on my cluster), Numpy, Scipy, Scikit-Learn, Matplotlib.
I've run most experiments with 4 GPUs.
The commands for running rotation experiments are
python main.py -d cifar10 -dc 160 -bs 128 -ngpu 4 -dr 0.3 -c 0 [-r]
python main.py -d stl10 -dc 64 -bs 64 -ngpu 4 -dr 0.3 -c 0 [-r]
where -c denotes the held out class, and -r would augment with rotation-prediction.
Similar usage applies for CPC, with -s for adding CPC as a task.
python main.py -d dog -c 0 [-s]
BibTex:
@proceedings{ahmed2019semantic,
title={Detecting semantic anomalies},
author={Ahmed, Faruk and Courville, Aaron},
booktitle={Proceedings of 34th AAAI Conference on Artificial Intelligence},
year={2020}
}