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Authors: David Duque-Arias 1 ; Santiago Velasco-Forero 1 ; Jean-Emmanuel Deschaud 1 ; François Goulette 1 ; Andres Serna 2 ; Etienne Decencière 1 and Beatriz Marcotegui 1

Affiliations: 1 MINES ParisTech, PSL Research University, France ; 2 Terra3D Research, Paris, France

Keyword(s): Loss Functions, Image Segmentation, Jaccard Loss, Deep Learning, U-Net Architecture.

Abstract: In this work, a new generalized loss function is proposed called power Jaccard to perform semantic segmentation tasks. It is compared with classical loss functions in different scenarios, including gray level and color image segmentation, as well as 3D point cloud segmentation. The results show improved performance, stability and convergence. We made available the code with our proposal with a demonstrative example.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Duque-Arias, D.; Velasco-Forero, S.; Deschaud, J.; Goulette, F.; Serna, A.; Decencière, E. and Marcotegui, B. (2021). On Power Jaccard Losses for Semantic Segmentation. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 561-568. DOI: 10.5220/0010304005610568

@conference{visapp21,
author={David Duque{-}Arias. and Santiago Velasco{-}Forero. and Jean{-}Emmanuel Deschaud. and Fran\c{C}ois Goulette. and Andres Serna. and Etienne Decencière. and Beatriz Marcotegui.},
title={On Power Jaccard Losses for Semantic Segmentation},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP},
year={2021},
pages={561-568},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010304005610568},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP
TI - On Power Jaccard Losses for Semantic Segmentation
SN - 978-989-758-488-6
IS - 2184-4321
AU - Duque-Arias, D.
AU - Velasco-Forero, S.
AU - Deschaud, J.
AU - Goulette, F.
AU - Serna, A.
AU - Decencière, E.
AU - Marcotegui, B.
PY - 2021
SP - 561
EP - 568
DO - 10.5220/0010304005610568
PB - SciTePress