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Modeling Drivers' Risk Perception via Attention to Improve Driving
  Assistance

Modeling Drivers' Risk Perception via Attention to Improve Driving Assistance

7 September 2024
Abhijat Biswas
John Gideon
Kimimasa Tamura
Guy Rosman
ArXiv (abs)PDFHTML

Papers citing "Modeling Drivers' Risk Perception via Attention to Improve Driving Assistance"

6 / 6 papers shown
Title
PlanT: Explainable Planning Transformers via Object-Level
  Representations
PlanT: Explainable Planning Transformers via Object-Level Representations
Katrin Renz
Kashyap Chitta
Otniel-Bogdan Mercea
A. Sophia Koepke
Zeynep Akata
Andreas Geiger
ViT
94
99
0
25 Oct 2022
Is Pseudo-Lidar needed for Monocular 3D Object detection?
Is Pseudo-Lidar needed for Monocular 3D Object detection?
Dennis Park
Rares Andrei Ambrus
Vitor Campagnolo Guizilini
Jie Li
Adrien Gaidon
MDE3DPC
97
319
0
13 Aug 2021
Large Scale Interactive Motion Forecasting for Autonomous Driving : The
  Waymo Open Motion Dataset
Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset
Scott Ettinger
Shuyang Cheng
Benjamin Caine
Chenxi Liu
Hang Zhao
...
Jiquan Ngiam
Vijay Vasudevan
Alexander McCauley
Jonathon Shlens
Drago Anguelov
192
566
0
20 Apr 2021
Learning to Track with Object Permanence
Learning to Track with Object Permanence
P. Tokmakov
Jie Li
Wolfram Burgard
Adrien Gaidon
VOT
91
206
0
26 Mar 2021
Analyzing the Variety Loss in the Context of Probabilistic Trajectory
  Prediction
Analyzing the Variety Loss in the Context of Probabilistic Trajectory Prediction
Luca Thiede
P. Brahma
63
62
0
23 Jul 2019
Predicting the Driver's Focus of Attention: the DR(eye)VE Project
Predicting the Driver's Focus of Attention: the DR(eye)VE Project
Andrea Palazzi
Davide Abati
Simone Calderara
Francesco Solera
Rita Cucchiara
68
253
0
10 May 2017
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