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Increasing the Robustness of Semantic Segmentation Models with
  Painting-by-Numbers

Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers

12 October 2020
Christoph Kamann
Burkhard Güssefeld
Robin Hutmacher
J. H. Metzen
Carsten Rother
ArXivPDFHTML

Papers citing "Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers"

5 / 5 papers shown
Title
Does Robustness on ImageNet Transfer to Downstream Tasks?
Does Robustness on ImageNet Transfer to Downstream Tasks?
Yutaro Yamada
Mayu Otani
OOD
23
27
0
08 Apr 2022
Benchmarking the Robustness of Instance Segmentation Models
Benchmarking the Robustness of Instance Segmentation Models
Said Fahri Altindis
Yusuf Dalva
Hamza Pehlivan
Aysegül Dündar
VLM
OOD
29
12
0
02 Sep 2021
Test-Time Adaptation to Distribution Shift by Confidence Maximization
  and Input Transformation
Test-Time Adaptation to Distribution Shift by Confidence Maximization and Input Transformation
Chaithanya Kumar Mummadi
Robin Hutmacher
K. Rambach
Evgeny Levinkov
Thomas Brox
J. H. Metzen
TTA
OOD
27
69
0
28 Jun 2021
StyleLess layer: Improving robustness for real-world driving
StyleLess layer: Improving robustness for real-world driving
Julien Rebut
Andrei Bursuc
P. Pérez
22
5
0
25 Mar 2021
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
178
932
0
21 Oct 2016
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