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Fool Me Once: Robust Selective Segmentation via Out-of-Distribution
  Detection with Contrastive Learning

Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning

1 March 2021
David S. W. Williams
Matthew Gadd
D. Martini
Paul Newman
    OODD
ArXivPDFHTML

Papers citing "Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning"

4 / 4 papers shown
Title
Lidar-level localization with radar? The CFEAR approach to accurate,
  fast and robust large-scale radar odometry in diverse environments
Lidar-level localization with radar? The CFEAR approach to accurate, fast and robust large-scale radar odometry in diverse environments
Daniel Adolfsson
Martin Magnusson
Anas W. Alhashimi
A. Lilienthal
Henrik Andreasson
36
40
0
04 Nov 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,683
0
05 Dec 2016
ENet: A Deep Neural Network Architecture for Real-Time Semantic
  Segmentation
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Adam Paszke
Abhishek Chaurasia
Sangpil Kim
Eugenio Culurciello
SSeg
235
2,059
0
07 Jun 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,156
0
06 Jun 2015
1