Crowd Counting Based on Multiresolution Density Map and Parallel Dilated Convolution
The current crowd counting tasks rely on a fully convolutional network to generate a density map that can achieve good performance. However, due to the crowd occlusion and perspective distortion in the image, the directly generated density map usually neglects the scale information and spatial conta...
Main Authors: | Jingfan Tang, Meijia Zhou, Pengfei Li, Min Zhang, Ming Jiang |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2021-01-01
|
Series: | Scientific Programming |
Online Access: | http://dx.doi.org/10.1155/2021/8831458 |
Similar Items
-
Crowd counting based on fusion of deep convolutional network and dilated convolution
by: SHENG Xinxin, et al.
Published: (2019-10-01) -
Redesigned Skip-Network for Crowd Counting with Dilated Convolution and Backward Connection
by: Sorn Sooksatra, et al.
Published: (2020-05-01) -
A High-Density Crowd Counting Method Based on Convolutional Feature Fusion
by: Hongling Luo, et al.
Published: (2018-11-01) -
Crowd Counting Method Based on Convolutional Neural Network With Global Density Feature
by: Zhi Liu, et al.
Published: (2019-01-01) -
Deep Dilated Convolutional Neural Network for Crowd Density Image Classification with Dataset Augmentation for Hajj Pilgrimage
by: Abdullah, J., et al.
Published: (2022)