Colour augmentation for improved semi-supervised semantic segmentation

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French, Geoffrey and Mackiewicz, Michal ORCID: https://orcid.org/0000-0002-8777-8880 (2022) Colour augmentation for improved semi-supervised semantic segmentation. In: Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 4). Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 4 . UNSPECIFIED, pp. 356-363.

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Abstract

Consistency regularization describes a class of approaches that have yielded state-of-the-art results for semi-supervised classification. While semi-supervised semantic segmentation proved to be more challenging, recent work has explored the challenges involved in using consistency regularization for segmentation problems and has presented solutions. In their self-supervised work Chen et al. found that colour augmentation prevents a classification network from using image colour statistics as a short-cut for self-supervised learning via instance discrimination. Drawing inspiration from this we find that a similar problem impedes semi-supervised semantic segmentation and offer colour augmentation as a solution, improving semi-supervised semantic segmentation performance on challenging photographic imagery. Implementation at: https://github.com/Britefury/cutmix-semisup-seg.

Item Type:	Book Section
Additional Information:	Funding Information: This work was funded under the European Union Horizon 2020 SMARTFISH project, grant agreement no. 773521. The computation required by this work was performed on the University of East Anglia HPC Cluster. Publisher Copyright: © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
Uncontrolled Keywords:	data augmentation,deep learning,semantic segmentation,semi-supervised learning,computer graphics and computer-aided design,computer vision and pattern recognition,human-computer interaction ,/dk/atira/pure/subjectarea/asjc/1700/1704
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Colour and Imaging Lab
Related URLs:	http://www.scopus.com/inward/record.url?... https://arxiv.org/abs/2110.04487
Depositing User:	LivePure Connector
Date Deposited:	24 May 2022 12:12
Last Modified:	04 Mar 2024 16:25
URI:	https://ueaeprints.uea.ac.uk/id/eprint/85050
DOI:	10.5220/0010807400003124

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