Cross-modal collaborative representation learning and a large-scale rgbt benchmark for crowd counting
Crowd counting is a fundamental yet challenging task, which desires rich information to
generate pixel-wise crowd density maps. However, most previous methods only used the …
generate pixel-wise crowd density maps. However, most previous methods only used the …
Deep learning based crowd counting model for drone assisted systems
Recent advances in deep learning make it possible to implement neural network
architecture fitted to the task. In this paper we present new deep neural network model …
architecture fitted to the task. In this paper we present new deep neural network model …
CCANet: A collaborative cross-modal attention network for RGB-D crowd counting
Y Liu, G Cao, B Shi, Y Hu - IEEE Transactions on Multimedia, 2023 - ieeexplore.ieee.org
Presently, to obtain a more accurate density map and crowd number, existing methods often
count by combining training RGB images and depth images. However, these methods are …
count by combining training RGB images and depth images. However, these methods are …
Density-aware and background-aware network for crowd counting via multi-task learning
X Liu, J Sang, W Wu, K Liu, Q Liu, X **a - Pattern Recognition Letters, 2021 - Elsevier
In this paper, we propose a density-aware and background-aware network via multi-task
learning (MTL-DB) for crowd counting. It aims to enable the model to capture the high-level …
learning (MTL-DB) for crowd counting. It aims to enable the model to capture the high-level …
A cross-modal crowd counting method combining CNN and cross-modal transformer
S Zhang, W Wang, W Zhao, L Wang, Q Li - Image and Vision Computing, 2023 - Elsevier
Cross-modal crowd counting aims to use the information between different modalities to
generate crowd density images, so as to estimate the number of pedestrians more …
generate crowd density images, so as to estimate the number of pedestrians more …
Clean vs. overlapped speech-music detection using harmonic-percussive features and multi-task learning
Detection of speech and music signals in isolated and overlapped conditions is an essential
preprocessing step for many audio applications. Speech signals have wavy and continuous …
preprocessing step for many audio applications. Speech signals have wavy and continuous …
Cross-modal collaborative representation and multi-level supervision for crowd counting
S Li, Z Hu, M Zhao, S Bi, Z Sun - Signal, Image and Video Processing, 2023 - Springer
Crowd features are often extracted from RGB images to complete the tasks of density
estimation and crowd counting. However, RGB images will be affected in some particularly …
estimation and crowd counting. However, RGB images will be affected in some particularly …
IoT and ML-Driven Smart Fire Alarm and Crowd Tracking
G Patil, B Kadam, V Gujalwar, V Patil… - … Conference on Advances …, 2024 - Springer
In response to the escalating global fire incidents, particularly in densely populated areas,
this research pioneers a vision-based fire detection system to overcome the limitations of …
this research pioneers a vision-based fire detection system to overcome the limitations of …
Research on 24‐Hour Dense Crowd Counting and Object Detection System Based on Multimodal Image Optimization Feature Fusion
G Ren, X Lu, Y Li - Scientific Programming, 2022 - Wiley Online Library
Motivation. In the environment of day and night video surveillance, in order to improve the
accuracy of machine vision dense crowd counting and target detection, this paper designs a …
accuracy of machine vision dense crowd counting and target detection, this paper designs a …
and Crowd Tracking
G Patil, B Kadam, V Gujalwar, V Patil… - … : Proceedings of AICTC …, 2024 - books.google.com
In response to the escalating global fire incidents, particularly in densely populated areas,
this research pioneers a vision-based fire detection system to overcome the limitations of …
this research pioneers a vision-based fire detection system to overcome the limitations of …