Density-Based Vehicle Counting with Unsupervised Scale Selection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F20%3APU138878" target="_blank" >RIV/00216305:26230/20:PU138878 - isvavai.cz</a>
Result on the web
<a href="http://www.dicta2020.org/wp-content/uploads/2020/09/22_CameraReady.pdf" target="_blank" >http://www.dicta2020.org/wp-content/uploads/2020/09/22_CameraReady.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/DICTA51227.2020.9363401" target="_blank" >10.1109/DICTA51227.2020.9363401</a>
Alternative languages
Result language
angličtina
Original language name
Density-Based Vehicle Counting with Unsupervised Scale Selection
Original language description
A significant hurdle within any counting task is the variance in scale of the objects to be counted. While size changes of some extent can be induced by perspective distortion, more severe scale differences can easily occur, e.g. in case of images taken by a drone from different elevations above the ground. The aim of our work is to overcome this issue by leveraging only lightweight dot annotations and a minimum level of training supervision. We propose a modification to the Stacked Hourglass network which enables the model to process multiple input scales and to automatically select the most suitable candidate using a quality score. We alter the training procedure to enable learning of the quality scores while avoiding their direct supervision, and thus without requiring any additional annotation effort. We evaluate our method on three standard datasets: PUCPR+, TRANCOS and CARPK. The obtained results are on par with current state-of-the-art methods while being more robust towards significant variations in input scale.
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Digital Image Computing: Techniques and Applications 2020
ISBN
978-1-7281-9108-9
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1-8
Publisher name
Institute of Electrical and Electronics Engineers
Place of publication
Melbourne
Event location
Melbourne
Event date
Nov 30, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000935148000034