Skip to Main content Skip to Navigation
Conference papers

On power Jaccard losses for semantic segmentation

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.
Complete list of metadata
Contributor : David DUQUE Connect in order to contact the contributor
Submitted on : Friday, February 12, 2021 - 2:18:36 PM
Last modification on : Wednesday, November 17, 2021 - 12:31:03 PM
Long-term archiving on: : Friday, May 14, 2021 - 9:32:47 AM


Files produced by the author(s)


  • HAL Id : hal-03139997, version 1


David Duque-Arias, Santiago Velasco-Forero, Jean-Emmanuel Deschaud, Francois Goulette, Andrés Serna, et al.. On power Jaccard losses for semantic segmentation. VISAPP 2021 : 16th International Conference on Computer Vision Theory and Applications, Feb 2021, Vienne (on line), Austria. ⟨hal-03139997⟩



Record views


Files downloads