Detail publikace

Pedestrian Detector Domain Shift Robustness Evaluation, and Domain Shift Error Mitigation Proposal

ZEMČÍK, T.

Originální název

Pedestrian Detector Domain Shift Robustness Evaluation, and Domain Shift Error Mitigation Proposal

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper evaluates daytime to nighttime traffic image domain shift on Faster R-CNN and SSD based pedestrian and cyclist detectors. Daytime image trained detectors are applied on a newly compiled nighttime image dataset and their performance is evaluated against detectors trained on both daytime and nighttime images. Faster R-CNN based detectors proved relatively robust, but still clearly inferior to the models trained on nighttime images, the SSD based model proved noncompetitive. Approaches to the domain shift deterioration mitigation were proposed and future work outlined.

Klíčová slova

Object detection, Pedestrian detection, Cyclist detection, ADAS, AV, Faster R-CNN, SSD, Domain shift, Domain adaptation, Data augmentation

Autoři

ZEMČÍK, T.

Vydáno

27. 4. 2021

Nakladatel

Brno University of Technology, Faculty of Electrical Engineering and Communication

Místo

Brno

ISBN

978-80-214-5943-4

Kniha

Proceedings II of the 27th student EEICT selected papers

Edice

1

Strany od

181

Strany do

187

Strany počet

7

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2021_sbornik_2_v3_DOI.pdf

BibTex

@inproceedings{BUT164116,
  author="Tomáš {Zemčík}",
  title="Pedestrian Detector Domain Shift Robustness Evaluation, and Domain Shift Error Mitigation Proposal",
  booktitle="Proceedings II of the 27th student EEICT selected papers",
  year="2021",
  series="1",
  pages="181--187",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno",
  doi="10.13164/eeict.2021.181",
  isbn="978-80-214-5943-4",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2021_sbornik_2_v3_DOI.pdf"
}