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On power Jaccard losses for semantic segmentation

Jean-Emmanuel Deschaud
Francois Goulette
Andrés Serna


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.
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hal-03139997 , version 1 (12-02-2021)


  • 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⟩
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