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Can We Trust You? On Calibration of a Probabilistic Object Detector for
  Autonomous Driving

Can We Trust You? On Calibration of a Probabilistic Object Detector for Autonomous Driving

26 September 2019
Di Feng
Lars Rosenbaum
Claudius Glaeser
Fabian Timm
Klaus C. J. Dietmayer
    UQCV3DPC
ArXiv (abs)PDFHTML

Papers citing "Can We Trust You? On Calibration of a Probabilistic Object Detector for Autonomous Driving"

24 / 24 papers shown
Calibrating the Full Predictive Class Distribution of 3D Object Detectors for Autonomous Driving
Calibrating the Full Predictive Class Distribution of 3D Object Detectors for Autonomous Driving
Cornelius Schröder
Marius-Raphael Schlüter
Markus Lienkamp
191
0
0
02 Oct 2025
How Safe Will I Be Given What I Saw? Calibrated Prediction of Safety Chances for Image-Controlled Autonomy
How Safe Will I Be Given What I Saw? Calibrated Prediction of Safety Chances for Image-Controlled Autonomy
Zhenjiang Mao
Mrinall Eashaan Umasudhan
Ivan Ruchkin
UQCV
269
1
0
12 Aug 2025
Run-time Monitoring of 3D Object Detection in Automated Driving Systems
  Using Early Layer Neural Activation Patterns
Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patterns
Hakan Yekta Yatbaz
M. Dianati
K. Koufos
Roger Woodman
3DPC
275
6
0
11 Apr 2024
Towards Calibrated Deep Clustering Network
Towards Calibrated Deep Clustering Network
Yuheng Jia
Jianhong Cheng
Hui Liu
Junhui Hou
UQCV
614
5
0
04 Mar 2024
Overcoming the Limitations of Localization Uncertainty: Efficient &
  Exact Non-Linear Post-Processing and Calibration
Overcoming the Limitations of Localization Uncertainty: Efficient & Exact Non-Linear Post-Processing and Calibration
Moussa Kassem Sbeyti
Michelle Karg
J. Dietrich
Azarm Nowzad
S. Albayrak
172
4
0
15 Jun 2023
Perception and Semantic Aware Regularization for Sequential Confidence
  Calibration
Perception and Semantic Aware Regularization for Sequential Confidence CalibrationComputer Vision and Pattern Recognition (CVPR), 2023
Zhenghua Peng
Yuanmao Luo
Tianshui Chen
Keke Xu
Shuangping Huang
AI4TS
422
4
0
31 May 2023
Probabilistic 3d regression with projected huber distribution
Probabilistic 3d regression with projected huber distribution
David Mohlin
Josephine Sullivan
167
0
0
09 Mar 2023
Parametric and Multivariate Uncertainty Calibration for Regression and
  Object Detection
Parametric and Multivariate Uncertainty Calibration for Regression and Object Detection
Fabian Küppers
Jonas Schneider
Anselm Haselhoff
UQCV
319
17
0
04 Jul 2022
LiDAR-MIMO: Efficient Uncertainty Estimation for LiDAR-based 3D Object
  Detection
LiDAR-MIMO: Efficient Uncertainty Estimation for LiDAR-based 3D Object Detection
Matthew A. Pitropov
Chengjie Huang
Vahdat Abdelzad
Krzysztof Czarnecki
Steven Waslander
3DPC
230
5
0
01 Jun 2022
$f$-Cal: Calibrated aleatoric uncertainty estimation from neural
  networks for robot perception
fff-Cal: Calibrated aleatoric uncertainty estimation from neural networks for robot perception
Dhaivat Bhatt
Kaustubh Mani
Dishank Bansal
Krishna Murthy Jatavallabhula
Hanju Lee
Liam Paull
UQCV
278
6
0
28 Sep 2021
Bayesian Confidence Calibration for Epistemic Uncertainty Modelling
Bayesian Confidence Calibration for Epistemic Uncertainty Modelling
Fabian Küppers
Jan Kronenberger
Jonas Schneider
Anselm Haselhoff
UQCVBDL
183
13
0
21 Sep 2021
How to Certify Machine Learning Based Safety-critical Systems? A
  Systematic Literature Review
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature ReviewInternational Conference on Automated Software Engineering (ASE), 2021
Florian Tambon
Gabriel Laberge
Le An
Amin Nikanjam
Paulina Stevia Nouwou Mindom
Y. Pequignot
Foutse Khomh
G. Antoniol
E. Merlo
François Laviolette
595
89
0
26 Jul 2021
Uncertainty for Identifying Open-Set Errors in Visual Object Detection
Uncertainty for Identifying Open-Set Errors in Visual Object DetectionIEEE Robotics and Automation Letters (RA-L), 2021
Dimity Miller
Niko Sünderhauf
Michael Milford
Feras Dayoub
EDL
277
54
0
03 Apr 2021
A Review of Testing Object-Based Environment Perception for Safe
  Automated Driving
A Review of Testing Object-Based Environment Perception for Safe Automated DrivingAutomotive Innovation (AI), 2021
Michael Hoss
Maike Scholtes
L. Eckstein
224
59
0
16 Feb 2021
Estimating and Evaluating Regression Predictive Uncertainty in Deep
  Object Detectors
Estimating and Evaluating Regression Predictive Uncertainty in Deep Object DetectorsInternational Conference on Learning Representations (ICLR), 2021
Ali Harakeh
Steven L. Waslander
UQCV
324
48
0
13 Jan 2021
From Black-box to White-box: Examining Confidence Calibration under
  different Conditions
From Black-box to White-box: Examining Confidence Calibration under different Conditions
Franziska Schwaiger
Maximilian Henne
Fabian Küppers
Felippe Schmoeller da Roza
Karsten Roscher
Anselm Haselhoff
166
11
0
08 Jan 2021
Labels Are Not Perfect: Inferring Spatial Uncertainty in Object
  Detection
Labels Are Not Perfect: Inferring Spatial Uncertainty in Object Detection
Di Feng
Zining Wang
Yiyang Zhou
Lars Rosenbaum
Fabian Timm
Klaus C. J. Dietmayer
Masayoshi Tomizuka
Wei Zhan
197
31
0
18 Dec 2020
Accurate 3D Object Detection using Energy-Based Models
Accurate 3D Object Detection using Energy-Based Models
Fredrik K. Gustafsson
Martin Danelljan
Thomas B. Schon
3DPC
401
11
0
08 Dec 2020
A Review and Comparative Study on Probabilistic Object Detection in
  Autonomous Driving
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving
Di Feng
Ali Harakeh
Steven Waslander
Klaus C. J. Dietmayer
AAMLUQCVEDL
403
299
0
20 Nov 2020
Labels Are Not Perfect: Improving Probabilistic Object Detection via
  Label Uncertainty
Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty
Di Feng
Lars Rosenbaum
Fabian Timm
Klaus C. J. Dietmayer
UQCV
236
6
0
10 Aug 2020
A Comparison of Uncertainty Estimation Approaches in Deep Learning
  Components for Autonomous Vehicle Applications
A Comparison of Uncertainty Estimation Approaches in Deep Learning Components for Autonomous Vehicle Applications
F. Arnez
H. Espinoza
A. Radermacher
Franccois Terrier
UQCV
347
33
0
26 Jun 2020
Inferring Spatial Uncertainty in Object Detection
Inferring Spatial Uncertainty in Object DetectionIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2020
Zining Wang
Di Feng
Yiyang Zhou
Lars Rosenbaum
Fabian Timm
Klaus C. J. Dietmayer
Masayoshi Tomizuka
Wei Zhan
409
29
0
07 Mar 2020
Leveraging Uncertainties for Deep Multi-modal Object Detection in
  Autonomous Driving
Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving
Di Feng
Yifan Cao
Lars Rosenbaum
Fabian Timm
Klaus C. J. Dietmayer
UQCV3DPC
337
24
0
01 Feb 2020
Deep Multi-modal Object Detection and Semantic Segmentation for
  Autonomous Driving: Datasets, Methods, and Challenges
Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges
Di Feng
Christian Haase-Schuetz
Lars Rosenbaum
Heinz Hertlein
Claudius Gläser
Fabian Duffhauss
W. Wiesbeck
Klaus C. J. Dietmayer
3DPC
798
1,279
0
21 Feb 2019
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