Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikačního výsledku
ZEMČÍK, T.
Originální název
Pedestrian Detector Domain Shift Robustness Evaluation, and Domain Shift Error Mitigation Proposal
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
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.
Anglický abstrakt
Klíčová slova
Object detection, Pedestrian detection, Cyclist detection, ADAS, AV, Faster R-CNN, SSD, Domain shift, Domain adaptation, Data augmentation
Klíčová slova v angličtině
Autoři
Rok RIV
2021
Vydáno
27.04.2021
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" }