Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation-Reference-Cited by-同舟云学术

Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Chan Robin¹,Rottmann Matthias¹,Gottschalk Hanno¹

Affiliation:

1. University of Wuppertal,IZMD, Faculty of Mathematics and Natural Sciences

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9709627/9709628/09711032.pdf?arnumber=9711032

Reference52 articles.

1. Do deep generative models know what they don’t know?;nalisnick;International Conference on Learning Representations,2019

2. Detecting the Unexpected via Image Resynthesis

3. Microsoft COCO: Common Objects in Context;lin;Computer-vision –ECCV 2014,2014

4. Enhancing the reliability of out-of-distribution image detection in neural networks;liang;International Conference on Learning Representations,2018

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