Single Image Crowd Counting (CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting)
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Updated
May 23, 2018 - Python
Single Image Crowd Counting (CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting)
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
Crowd counting on the ShanghaiTech dataset, using multi-column convolutional neural networks.
GCC dataset Collector and Labeler (GCC CL) [CVPR2019]
Single Image Crowd Counting via MCNN (Unofficial Implementation)
This is the implementation of paper "A Multi-Scale and Multi-level Feature Aggregation Network for Crowd Counting"
Multi-level Attention Refined UNet for crowd counting
The code for our ECCV 2020 paper: Estimating People Flows to Better Count Them in Crowded Scenes
LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.
A modified version of OpenLTE able to extract Channel State Information (CSI) from LTE signals.
A modified version of the LTE Scanner supporting RTL-SDR/HackRF/BladeRF and able to extract Channel State Information (CSI) from LTE signals.
SOFT-CSRNET : Counting people in drone video footage
Developed Counting Convolutional Neural Network (CCNN) for Crowd Counting- Deep Neural Network Course Project
Using transfer learning on pretrained image models to learn density map generation and count the number of people in an image.
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