W Shu, J Wan, KC Tan, S Kwong… - Proceedings of the …, 2022 - openaccess.thecvf.com
This paper investigates crowd counting in the frequency domain, which is a novel direction compared to the traditional view in the spatial domain. By transforming the density map into …
In today's scenario, there are frequent events (viz. political rallies, live concerts, strikes, sports meet) occur in which many people gather to participate in the event. In crowded areas …
Cameras in modern devices such as smartphones, satellites and medical equipment are capable of capturing very high resolution images and videos. Such high-resolution data …
Recently, indiscernible scene understanding has attracted a lot of attention in the vision community. We further advance the frontier of this field by systematically studying a new …
Y Pang, Z Ni, X Zhong - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Crowd counting in smart surveillance systems plays a crucial role in Internet of Things (IoT) and smart cities, and can affect various aspects, such as public safety, crowd management …
Supervised crowd counting relies on manual labeling, which is costly and time-consuming. This led to an increased interest in unsupervised methods. However, there is a significant …
W Shu, J Wan, AB Chan - IEEE Transactions on Pattern …, 2023 - ieeexplore.ieee.org
Typical approaches that learn crowd density maps are limited to extracting the supervisory information from the loosely organized spatial information in the crowd dot/density maps …
In this article, we propose a simple yet effective approach, called point adversarial self mining (PASM), to improve the recognition accuracy in facial expression recognition (FER) …
Domain adaptation is commonly employed in crowd counting to bridge the domain gaps between different datasets. However, existing domain adaptation methods tend to focus on …