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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Updated
Nov 27, 2022 - Python
Using transfer learning on pretrained image models to learn density map generation and count the number of people in an image.
Developed Counting Convolutional Neural Network (CCNN) for Crowd Counting- Deep Neural Network Course Project
This machine learning project uses computer vision techniques to count the number of people entering and exiting a mall.
This repository performs crowd counting inference using a pre-trained ONNX model. Input an image to estimate head localization in crowded scenes.
GCC dataset Collector and Labeler (GCC CL) [CVPR2019]
This is the implementation of paper "A Multi-Scale and Multi-level Feature Aggregation Network for Crowd Counting"
A modified version of OpenLTE able to extract Channel State Information (CSI) from LTE signals.
ComPtr: Towards Diverse Bi-source Dense Prediction Tasks via A Simple yet General Complementary Transformer
SOFT-CSRNET : Counting people in drone video footage
[ICCV 2023] Point-Query Quadtree for Crowd Counting, Localization, and More
A modified version of the LTE Scanner supporting RTL-SDR/HackRF/BladeRF and able to extract Channel State Information (CSI) from LTE signals.
Multi-level Attention Refined UNet for crowd counting
LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.
Crowd counting on the ShanghaiTech dataset, using multi-column convolutional neural networks.
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