Multimodal Crowd Counting with Pix2Pix GANs

Muhammad Asif Khan, Hamid Menouar, Ridha Hamila

2024

Abstract

Most state-of-the-art crowd counting methods use color (RGB) images to learn the density map of the crowd. However, these methods often struggle to achieve higher accuracy in densely crowded scenes with poor illumination. Recently, some studies have reported improvement in the accuracy of crowd counting models using a combination of RGB and thermal images. Although multimodal data can lead to better predictions, multimodal data might not be always available beforehand. In this paper, we propose the use of generative adversarial networks (GANs) to automatically generate thermal infrared (TIR) images from color (RGB) images and use both to train crowd counting models to achieve higher accuracy. We use a Pix2Pix GAN network first to translate RGB images to TIR images. Our experiments on several state-of-the-art crowd counting models and benchmark crowd datasets report significant improvement in accuracy.

Paper Citation

in Harvard Style

Khan M., Menouar H. and Hamila R. (2024). Multimodal Crowd Counting with Pix2Pix GANs. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 806-813. DOI: 10.5220/0012547900003660

in Bibtex Style

@conference{visapp24,
author={Muhammad Asif Khan and Hamid Menouar and Ridha Hamila},
title={Multimodal Crowd Counting with Pix2Pix GANs},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={806-813},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012547900003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Multimodal Crowd Counting with Pix2Pix GANs
SN - 978-989-758-679-8
AU - Khan M.
AU - Menouar H.
AU - Hamila R.
PY - 2024
SP - 806
EP - 813
DO - 10.5220/0012547900003660
PB - SciTePress