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The Lovász-Softmax loss: A tractable surrogate for the optimization of
  the intersection-over-union measure in neural networks

The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks

24 May 2017
Maxim Berman
Amal Rannen Triki
Matthew B. Blaschko
    SSeg
ArXivPDFHTML

Papers citing "The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks"

3 / 3 papers shown
Title
Effect of the output activation function on the probabilities and errors
  in medical image segmentation
Effect of the output activation function on the probabilities and errors in medical image segmentation
Lars Nieradzik
G. Scheuermann
D. Saur
Christina Gillmann
SSeg
MedIm
UQCV
37
6
0
02 Sep 2021
STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos
STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos
A. Athar
Sabarinath Mahadevan
Aljosa Osep
Laura Leal-Taixé
Bastian Leibe
VOS
77
170
0
18 Mar 2020
Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers
Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers
Stephan R. Richter
Stefan Roth
3DV
28
139
0
29 Apr 2018
1