Two-stream Adaptive Convolutional Neural Network for Crowd Counting
Abstract
References
Recommendations
Research on Crowd Counting Algorithm Based on Multi-scale Adaptive Network
AIPR '21: Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern RecognitionThe variable spatial scale and crowd distribution in crowd images are the main challenges faced by crowd counting problems in recent years. In order to solve the above problems, a crowd counting method based on a multi-scale adaptive network is proposed ...
Dense crowd counting from still images with convolutional neural networks
We propose a deep learning method for people counting.We provide a new crowd dataset called AHU-CROWD.We test our method on UCSD and UCF-CROWD and compare with the state-of-the-art. For reasons of public security, modeling large crowd distributions for ...
Atrous convolutions spatial pyramid network for crowd counting and density estimation
AbstractScale variation because of perspective distortion is still a challenge for crowd analysis. To address this problem, an atrous convolutions spatial pyramid network (ACSPNet) is proposed to perform crowd counts and density maps for both ...
Comments
Information & Contributors
Information
Published In

Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 46Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format