Crowd Counting: A view around state-of-the-art
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Updated
Dec 23, 2023 - Jupyter Notebook
Crowd Counting: A view around state-of-the-art
Address the crowd counting problem on the Mall dataset (sparse) by exploring regression-based (Xception) and density-based (CSRNet) approaches.
Crowd Counting Via Scale-adaptive Convolutional Neural Network
Securely and privately verifiable protests
SE project for crowd management at POS terminals
An experiment in open-ended publishing
Developed Counting Convolutional Neural Network (CCNN) for Crowd Counting- Deep Neural Network Course Project
Welcome to the Crowd Counter program! This Python application utilizes the p2pnet model to calculate the number of people in a crowd based on an input image. The program marks each and every entity in the crowd with a point and provides the total count of individuals as the program output. 🙆♂️🙆♀️
Keras based implementation of the CSRNET model
Crowd Counting - From Real to Synthetic Datasets
An intelligent system to disable gathering during pandemic
fast visual object counting via example-based density estimation
Data preprocessing & augmentation framework, designed for working with crowd counting datasets, ML/DL framework-independent. Supports multitude of simple as well as advanced transformations, outputs and loaders, all of them to be combined using pipelines.
Project page for "OmniCount: Multi-label Object Counting with Semantic-Geometric Priors"
This repository contains the implementation of a wide variety of Deep Learning Projects in different applications of computer vision, NLP, federated, and distributed learning. These projects include university projects and projects implemented due to interest in Deep Learning.
A simple crowd density baseline models using pytorch
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