Single Image Crowd Counting via MCNN (Unofficial Implementation)

Single Image Crowd Counting (CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting)

The code for our ECCV 2020 paper: Estimating People Flows to Better Count Them in Crowded Scenes

[ICCV 2023] Point-Query Quadtree for Crowd Counting, Localization, and More

LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.

使用OpenCV部署P2PNet人群检测和计数，包含C++和Python两种版本的实现

Multi-level Attention Refined UNet for crowd counting

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

A modified version of the LTE Scanner supporting RTL-SDR/HackRF/BladeRF and able to extract Channel State Information (CSI) from LTE signals.

Crowd counting on the ShanghaiTech dataset, using multi-column convolutional neural networks.

SOFT-CSRNET : Counting people in drone video footage

Pytorch implementation of SGANet for crowd counting

This is the implementation of paper "A Multi-Scale and Multi-level Feature Aggregation Network for Crowd Counting"

unofficial keras port of LSC-CNN

ComPtr: Towards Diverse Bi-source Dense Prediction Tasks via A Simple yet General Complementary Transformer

A modified version of OpenLTE able to extract Channel State Information (CSI) from LTE signals.

A simple label tool for crowd counting.

Crowd Conting on Drone Data

Using transfer learning on pretrained image models to learn density map generation and count the number of people in an image.