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Multi-task Learning with Attention for End-to-end Autonomous Driving

Multi-task Learning with Attention for End-to-end Autonomous Driving

21 April 2021
Keishi Ishihara
Anssi Kanervisto
J. Miura
Ville Hautamaki
ArXivPDFHTML

Papers citing "Multi-task Learning with Attention for End-to-end Autonomous Driving"

12 / 12 papers shown
Title
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
Yuxiang Lu
Shengcao Cao
Yu-xiong Wang
49
1
0
18 Oct 2024
Guiding Attention in End-to-End Driving Models
Guiding Attention in End-to-End Driving Models
Diego Porres
Yi Xiao
Gabriel Villalonga
Alexandre Levy
Antonio M. López
26
0
0
30 Apr 2024
LeTFuser: Light-weight End-to-end Transformer-Based Sensor Fusion for
  Autonomous Driving with Multi-Task Learning
LeTFuser: Light-weight End-to-end Transformer-Based Sensor Fusion for Autonomous Driving with Multi-Task Learning
Pedram Agand
Mohammad Mahdavian
Manolis Savva
Mo Chen
ViT
26
4
0
19 Oct 2023
DeepIPCv2: LiDAR-powered Robust Environmental Perception and
  Navigational Control for Autonomous Vehicle
DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle
Oskar Natan
J. Miura
3DPC
28
1
0
13 Jul 2023
DiRaC-I: Identifying Diverse and Rare Training Classes for Zero-Shot
  Learning
DiRaC-I: Identifying Diverse and Rare Training Classes for Zero-Shot Learning
Sandipan Sarma
Arijit Sur
VLM
24
1
0
31 Dec 2022
DeepIPC: Deeply Integrated Perception and Control for an Autonomous
  Vehicle in Real Environments
DeepIPC: Deeply Integrated Perception and Control for an Autonomous Vehicle in Real Environments
Oskar Natan
J. Miura
32
1
0
20 Jul 2022
Trajectory-guided Control Prediction for End-to-end Autonomous Driving:
  A Simple yet Strong Baseline
Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
Peng Wu
Xiaosong Jia
Li Chen
Junchi Yan
Hongyang Li
Yu Qiao
30
182
0
16 Jun 2022
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
Marvin Klingner
Konstantin Müller
Mona Mirzaie
Jasmin Breitenstein
Jan-Aike Termöhlen
Tim Fingscheidt
19
4
0
01 Jun 2022
Compressed Hierarchical Representations for Multi-Task Learning and Task
  Clustering
Compressed Hierarchical Representations for Multi-Task Learning and Task Clustering
João Machado de Freitas
Sebastian Berg
Bernhard C. Geiger
Manfred Mücke
14
1
0
31 May 2022
End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and
  Multi-agent
End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and Multi-agent
Oskar Natan
J. Miura
20
34
0
12 Apr 2022
Vision Transformer for Learning Driving Policies in Complex Multi-Agent
  Environments
Vision Transformer for Learning Driving Policies in Complex Multi-Agent Environments
E. Kargar
Ville Kyrki
ViT
21
12
0
14 Sep 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
950
20,567
0
17 Apr 2017
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