A Unified Framework for Self-Supervised Outlier Detection
SSD: A Unified Framework for Self-Supervised Outlier Detection [ICLR 2021]
Pdf: https://openreview.net/forum?id=v5gjXpmR8J
Code for our ICLR 2021 paper on outlier detection, titled SSD, without requiring class labels of in-distribution training data. We leverage recent advances in self-supervised representation learning followed by the cluster-based outlier detection to achieve competitive performance. This repository support both self-supervised training of networks and outlier detection evaluation of pre-trained networks. It also includes code for the two proposed extensions in the paper, i.e., 1) Few-shot outlier detection and 2) Extending SSD by including class labels, when available.
Getting started
Let’s start by installing all dependencies.
pip install -r requirement.txt
Outlier detection with a pre-trained classifier
This is how we can evaluate the performance of a pre-trained ResNet50 classifier trained using SimCLR