ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2003.02425
  4. Cited By
Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk
  Object Identification via Causal Inference

Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference

5 March 2020
Chengxi Li
Stanley H. Chan
Yi-Ting Chen
    CML
ArXivPDFHTML

Papers citing "Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference"

27 / 27 papers shown
Title
Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving
Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving
Shahin Atakishiyev
Mohammad Salameh
Randy Goebel
100
6
0
18 Mar 2024
Urban Driving with Conditional Imitation Learning
Urban Driving with Conditional Imitation Learning
Jeffrey Hawke
Richard Shen
Corina Gurau
Siddharth Sharma
Daniele Reda
...
Przemyslaw Mazur
Sean Micklethwaite
Nicolas Griffiths
Amar Shah
Alex Kendall
87
147
0
30 Nov 2019
Grounding Human-to-Vehicle Advice for Self-driving Vehicles
Grounding Human-to-Vehicle Advice for Self-driving Vehicles
Jinkyu Kim
Teruhisa Misu
Yi-Ting Chen
Ashish Tawari
John F. Canny
32
101
0
16 Nov 2019
A Self Validation Network for Object-Level Human Attention Estimation
A Self Validation Network for Object-Level Human Attention Estimation
Zehua Zhang
Chen Yu
David J. Crandall
EgoV
37
10
0
31 Oct 2019
Causal Induction from Visual Observations for Goal Directed Tasks
Causal Induction from Visual Observations for Goal Directed Tasks
Sunjay Cauligi
Yuke Zhu
D. Stefan
Tamara Rezk
CML
LRM
35
63
0
03 Oct 2019
Learning Neural Causal Models from Unknown Interventions
Learning Neural Causal Models from Unknown Interventions
Nan Rosemary Ke
O. Bilaniuk
Anirudh Goyal
Stefan Bauer
Hugo Larochelle
Bernhard Schölkopf
Michael C. Mozer
C. Pal
Yoshua Bengio
CML
OOD
61
168
0
02 Oct 2019
Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph
  Convolutional Networks
Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks
Chengxi Li
Yue Meng
Stanley H. Chan
Yi-Ting Chen
GNN
18
61
0
20 Sep 2019
Context Aware Road-user Importance Estimation (iCARE)
Context Aware Road-user Importance Estimation (iCARE)
Alireza Rahimpour
Sujitha Martin
Ashish Tawari
Hairong Qi
25
6
0
30 Aug 2019
Goal-oriented Object Importance Estimation in On-road Driving Videos
Goal-oriented Object Importance Estimation in On-road Driving Videos
M. Gao
Ashish Tawari
Sujitha Martin
18
26
0
08 May 2019
Exploring the Limitations of Behavior Cloning for Autonomous Driving
Exploring the Limitations of Behavior Cloning for Autonomous Driving
Felipe Codevilla
Eder Santana
Antonio M. López
Adrien Gaidon
15
535
0
18 Apr 2019
Partial Convolution based Padding
Partial Convolution based Padding
Guilin Liu
Kevin J. Shih
Ting-Chun Wang
F. Reda
Karan Sapra
Zhiding Yu
Andrew Tao
Bryan Catanzaro
VLM
58
91
0
28 Nov 2018
Temporal Recurrent Networks for Online Action Detection
Temporal Recurrent Networks for Online Action Detection
Mingze Xu
M. Gao
Yi-Ting Chen
L. Davis
David J. Crandall
OffRL
53
163
0
18 Nov 2018
Deep Object-Centric Policies for Autonomous Driving
Deep Object-Centric Policies for Autonomous Driving
Dequan Wang
Coline Devin
Qi-Zhi Cai
Feng Yu
Trevor Darrell
OCL
32
100
0
13 Nov 2018
Toward Driving Scene Understanding: A Dataset for Learning Driver
  Behavior and Causal Reasoning
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning
Vasili Ramanishka
Yi-Ting Chen
Teruhisa Misu
Kate Saenko
49
279
0
06 Nov 2018
Image Inpainting for Irregular Holes Using Partial Convolutions
Image Inpainting for Irregular Holes Using Partial Convolutions
Guilin Liu
F. Reda
Kevin J. Shih
Ting-Chun Wang
Andrew Tao
Bryan Catanzaro
176
1,919
0
20 Apr 2018
Predicting Driver Attention in Critical Situations
Predicting Driver Attention in Critical Situations
Ye Xia
Danqing Zhang
Jinkyu Kim
K. Nakayama
K. Zipser
D. Whitney
44
133
0
17 Nov 2017
End-to-end Driving via Conditional Imitation Learning
End-to-end Driving via Conditional Imitation Learning
Felipe Codevilla
Matthias Muller
Antonio M. López
V. Koltun
Alexey Dosovitskiy
87
1,062
0
06 Oct 2017
Agent-Centric Risk Assessment: Accident Anticipation and Risky Region
  Localization
Agent-Centric Risk Assessment: Accident Anticipation and Risky Region Localization
Kuo-Hao Zeng
Shih-Han Chou
Fu-Hsiang Chan
Juan Carlos Niebles
Min Sun
42
60
0
18 May 2017
Interpretable Learning for Self-Driving Cars by Visualizing Causal
  Attention
Interpretable Learning for Self-Driving Cars by Visualizing Causal Attention
Jinkyu Kim
John F. Canny
FAtt
XAI
OOD
MILM
CML
61
334
0
30 Mar 2017
Simple Online and Realtime Tracking with a Deep Association Metric
Simple Online and Realtime Tracking with a Deep Association Metric
N. Wojke
Alex Bewley
Dietrich Paulus
VOT
365
3,492
0
21 Mar 2017
Mask R-CNN
Mask R-CNN
Kaiming He
Georgia Gkioxari
Piotr Dollár
Ross B. Girshick
ObjD
227
27,018
0
20 Mar 2017
End-to-end Learning of Driving Models from Large-scale Video Datasets
End-to-end Learning of Driving Models from Large-scale Video Datasets
Huazhe Xu
Yang Gao
Feng Yu
Trevor Darrell
62
824
0
04 Dec 2016
End to End Learning for Self-Driving Cars
End to End Learning for Self-Driving Cars
Mariusz Bojarski
D. Testa
Daniel Dworakowski
Bernhard Firner
B. Flepp
...
Urs Muller
Jiakai Zhang
Xin Zhang
Jake Zhao
Karol Zieba
SSL
30
4,153
0
25 Apr 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on
  Learning
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
Sergey Ioffe
Vincent Vanhoucke
Alexander A. Alemi
229
14,196
0
23 Feb 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
316
149,474
0
22 Dec 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
749
39,383
0
01 Sep 2014
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
136
43,290
0
01 May 2014
1