• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. EvCenterNet: Uncertainty Estimation for Object Detection Using Evidential Learning
 
  • Details
  • Full
Options
2023
Conference Paper
Title

EvCenterNet: Uncertainty Estimation for Object Detection Using Evidential Learning

Abstract
Uncertainty estimation is crucial in safety-critical settings such as automated driving as it provides valuable information for several downstream tasks including high-level decision making and path planning. In this work, we propose EvCenterNet, a novel uncertainty-aware 2D object detection framework using evidential learning to directly estimate both classification and regression uncertainties. To employ evidential learning for object detection, we devise a combination of evidential and focal loss functions for the sparse heatmap inputs. We introduce class-balanced weighting for regression and heatmap prediction to tackle the class imbalance encountered by evidential learning. Moreover, we propose a learning scheme to actively utilize the predicted heatmap uncertainties to improve the detection performance by focusing on the most uncertain points. We train our model on the KITTI dataset and evaluate it on challenging out-of-distribution datasets including BDD100K and nuImages. Our experiments demonstrate that our approach improves the precision and minimizes the execution time loss in relation to the base model.
Author(s)
Nallapareddy, Monish R.
Fraunhofer-Institut für Kognitive Systeme IKS  
Sirohi, Kshitij
University of Freiburg
Drews, Paulo L.J.
University of Freiburg
Burgard, Wolfram
University of Technology Nuremberg
Cheng, Chih-Hong
Fraunhofer-Institut für Kognitive Systeme IKS  
Valada, Abhinav
University of Freiburg
Mainwork
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2023  
Project(s)
IKS-Ausbauprojekt  
Funder
Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie  
Conference
International Conference on Intelligent Robots and Systems 2023  
Open Access
DOI
10.1109/IROS55552.2023.10341826
Language
English
Fraunhofer-Institut für Kognitive Systeme IKS  
Fraunhofer Group
Fraunhofer-Verbund IUK-Technologie  
Keyword(s)
  • heating system

  • three-dimensional display

  • estimation

  • focusing

  • object detection

  • uncertainty estimation

  • automated driving

  • heatmap

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024