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On the Choice of Data for Efficient Training and Validation of
  End-to-End Driving Models

On the Choice of Data for Efficient Training and Validation of End-to-End Driving Models

1 June 2022
Marvin Klingner
Konstantin Müller
Mona Mirzaie
Jasmin Breitenstein
Jan-Aike Termöhlen
Tim Fingscheidt
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Papers citing "On the Choice of Data for Efficient Training and Validation of End-to-End Driving Models"

3 / 3 papers shown
Title
Learning to drive from a world on rails
Learning to drive from a world on rails
Di Chen
V. Koltun
Philipp Krahenbuhl
98
116
0
03 May 2021
Multi-task Learning with Attention for End-to-end Autonomous Driving
Multi-task Learning with Attention for End-to-end Autonomous Driving
Keishi Ishihara
Anssi Kanervisto
J. Miura
Ville Hautamaki
39
60
0
21 Apr 2021
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Ajay Jain
Sergio Casas
Renjie Liao
Yuwen Xiong
Song Feng
Sean Segal
R. Urtasun
149
73
0
17 Oct 2019
1