Evaluation of Out-of-Distribution Detection Performance of Self-Supervised Learning in a Controllable Environment

• URL: http://arxiv.org/abs/2011.13120v2
• Date: Mon, 18 Oct 2021 13:22:24 GMT
• Title: Evaluation of Out-of-Distribution Detection Performance of Self-Supervised Learning in a Controllable Environment
• Authors: Jeonghoon Park, Kyungmin Jo, Daehoon Gwak, Jimin Hong, Jaegul Choo, Edward Choi
• Abstract summary: We evaluate the out-of-distribution (OOD) detection performance of self-supervised learning (SSL) techniques with a new evaluation framework. Unlike the previous evaluation methods, the proposed framework adjusts the distance of OOD samples from the in-distribution samples.
• Score: 27.28750644075659
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We evaluate the out-of-distribution (OOD) detection performance of self-supervised learning (SSL) techniques with a new evaluation framework. Unlike the previous evaluation methods, the proposed framework adjusts the distance of OOD samples from the in-distribution samples. We evaluate an extensive combination of OOD detection algorithms on three different implementations of the proposed framework using simulated samples, images, and text. SSL methods consistently demonstrated the improved OOD detection performance in all evaluation settings.

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