CrowdFormer: Weakly-supervised crowd counting with improved generalizability Convolutional neural networks (CNNs) have dominated the field of computer vision for nearly a decade. However, due to their limited receptive field, CNNs f... SS Savner,V Kanhangad - 《Journal of Visual Communication & Im...
To solve this problem, a crowd counting method based on a self-attention residual network is proposed. First, a multiscale convolution module composed of dilated convolution and deformation convolution is used. To avoid losing image resolution, some of the sampling positions are shifted to the ...
Crowd counting and density estimation is still one of the important task in video surveillance. Usually a regression based method is used to estimate the number of people from a sequence of images. In this paper we investigate to estimate the count of people in a crowded scene. We detect the...
This project is an implementation of the crowd counting model proposed in our CVPR 2017 paper - Switching Convolutional Neural Network(SCNN) for Crowd Counting. SCNN is an adaptation of the fully-convolutional neural network and uses an expert CNN that
This repository contains the code for the Curriculum Learning (CL) based algorithm for crowd counting, as described in our paper "Optimizing Crowd Counting in Dense Environments through Curriculum Learning Training Strategy". If you use it, please cite it: @article{, title={Optimizing Crowd Countin...
Muhammad Arif, Sultan Daud, Saleh Basalamah(2012), ―Counting of People in the Extremely Dense Crowd using Genetic Algorithm and Blobs Counting‖, IAES International Journal of Artificial Intelligence (IJ-AI), 2(2): 1-8.Arif, M., Daud, S., & Basalamah, S. (2013). Counting of people ...
Crowding counting research evolves quickly by the lever-age of development in deep learning. Many researchers put their efforts into crowd counting tasks and have achieved many significant improvements. However, current datasets still barely satisfy this evolution and high quality evaluation data is urgen...
This distance can be calculated by counting how many times you spin the roulette wheel. Experts say that even if you lose a lot of money if you play for at least 200 spins, your capital will be restored. Decide on your goals and stick to them. Prior to devising a slot machine ...
model.py add implementation May 4, 2022 Repository files navigation README Code for "Leveraging Self-Supervision for Cross-Domain Crowd Counting" (CVPR 2022) This repository is a PyTorch implementation for the paperLeveraging Self-Supervision for Cross-Domain Crowd Counting, which is accepted asoral...
This allows us to address the problem of limited size of existing datasets for crowd counting. We collect two crowd scene datasets from Google using keyword searches and queryby-example image retrieval, respectively. We demonstrate how to efficiently learn from these unlabeled datasets by ...