Pedestrian Detector Domain Shift Robustness Evaluation, and Domain Shift Error Mitigation Proposal
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU136560" target="_blank" >RIV/00216305:26220/21:PU136560 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Pedestrian Detector Domain Shift Robustness Evaluation, and Domain Shift Error Mitigation Proposal
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings II of the 27th student EEICT
ISBN
978-80-214-5943-4
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
1-7
Publisher name
Vysoké učené Technické, Fakulta elektrotechniky a komunikačních technologií
Place of publication
Brno
Event location
Brno
Event date
Apr 27, 2021
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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