Single Image Crowd Counting via MCNN (Unofficial Implementation)
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Updated
Apr 7, 2020 - Python
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
Multi-level Attention Refined UNet for crowd counting
Crowd counting on the ShanghaiTech dataset, using multi-column convolutional neural networks.
This is the implementation of paper "A Multi-Scale and Multi-level Feature Aggregation Network for Crowd Counting"
Using transfer learning on pretrained image models to learn density map generation and count the number of people in an image.
This repository performs crowd counting inference using a pre-trained ONNX model. Input an image to estimate head localization in crowded scenes.
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