AVMSN: An Audio-Visual Two Stream Crowd Counting Framework Under Low-Quality Conditions

AVMSN: An Audio-Visual Two Stream Crowd Counting Framework Under Low-Quality Conditions

Crowd counting is considered as the essential computer vision application that uses the convolutional neural network to model the crowd density as the regression task. However, the vision-based models are hard to extract the feature under low-quality conditions. As we know, visual and audio are used...

Full description

Bibliographic Details
Main Authors: Ruihan Hu, Qinglong Mo, Yuanfei Xie, Yongqian Xu, Jiaqi Chen, Yalun Yang, Hongjian Zhou, Zhi-Ri Tang, Edmond Q. Wu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Multi-scale architecture
audio-visual model
cascade fusion
crowd counting
Online Access:https://ieeexplore.ieee.org/document/9416332/

Internet

https://ieeexplore.ieee.org/document/9416332/

Similar Items