Object Tracking and Detection Using OpenCV

Last update: Aug 21, 2022

Overview

Object-Tracking-and-Detection-Using-OpenCV

Object tracking is one such application of computer vision where an object is detected in a video, otherwise interpreted as a set of frames, and the object’s trajectory is estimated. For instance, you have a video of a baseball match, and you want to track the ball’s location constantly throughout the video.

OpenCV-based object tracking

Object tracking using OpenCV is a popular method that is extensively used in the domain. OpenCV has a number of built-in functions specifically designed for the purpose of object tracking. Some object trackers in OpenCV include MIL, CSRT, GOTURN, and MediandFlow. Selecting a specific tracker depends on the application you are trying to design. Each tracker has its advantages and disadvantages, and a single type of tracker is not desired in all the applications.

Owner

Happy N. Monday

GitHub Repository

Unofficial PyTorch Implementation of AHDRNet (CVPR 2019)

AHDRNet-PyTorch This is the PyTorch implementation of Attention-guided Network for Ghost-free High Dynamic Range Imaging (CVPR 2019). The official cod

4 Sep 08, 2022

Open-sourcing the Slates Dataset for recommender systems research

FINN.no Recommender Systems Slate Dataset This repository accompany the paper "Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sa

48 Nov 28, 2022

Object-Centric Learning with Slot Attention

Slot Attention This is a re-implementation of "Object-Centric Learning with Slot Attention" in PyTorch (https://arxiv.org/abs/2006.15055). Requirement

72 Jan 02, 2023

A PyTorch implementation of EventProp [https://arxiv.org/abs/2009.08378], a method to train Spiking Neural Networks

Spiking Neural Network training with EventProp This is an unofficial PyTorch implemenation of EventProp, a method to compute exact gradients for Spiki

35 Jul 29, 2022

Framework for evaluating ANNS algorithms on billion scale datasets.

Billion-Scale ANN http://big-ann-benchmarks.com/ Install The only prerequisite is Python (tested with 3.6) and Docker. Works with newer versions of Py

132 Dec 24, 2022

AutoDeeplab / auto-deeplab / AutoML for semantic segmentation, implemented in Pytorch

AutoML for Image Semantic Segmentation Currently this repo contains the only working open-source implementation of Auto-Deeplab which, by the way out-

299 Dec 17, 2022

Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)

DQC: Differentiable Quantum Chemistry Differentiable quantum chemistry package. Currently only support differentiable density functional theory (DFT)

75 Dec 02, 2022

PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers

CvT: Introducing Convolutions to Vision Transformers Pytorch implementation of CvT: Introducing Convolutions to Vision Transformers Usage: img = torch

193 Jan 03, 2023

Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

GAN stability This repository contains the experiments in the supplementary material for the paper Which Training Methods for GANs do actually Converg

885 Jan 01, 2023

Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)

1k Jan 03, 2023

An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding, top-down-bottom-up, and attention (consensus between columns)

GLOM - Pytorch (wip) An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding,

173 Dec 14, 2022

Object Tracking and Detection Using OpenCV

Related tags

Overview

Object-Tracking-and-Detection-Using-OpenCV

OpenCV-based object tracking

Owner

Happy N. Monday

Unofficial PyTorch Implementation of AHDRNet (CVPR 2019)

Open-sourcing the Slates Dataset for recommender systems research

Object-Centric Learning with Slot Attention

A PyTorch implementation of EventProp [https://arxiv.org/abs/2009.08378], a method to train Spiking Neural Networks

Framework for evaluating ANNS algorithms on billion scale datasets.

AutoDeeplab / auto-deeplab / AutoML for semantic segmentation, implemented in Pytorch

Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)

PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers

Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)

An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding, top-down-bottom-up, and attention (consensus between columns)

Training and Evaluation Code for Neural Volumes

a reimplementation of LiteFlowNet in PyTorch that matches the official Caffe version

Intrusion Detection System using ensemble learning (machine learning)

Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"

Embracing Single Stride 3D Object Detector with Sparse Transformer

Aligning Latent and Image Spaces to Connect the Unconnectable

Learning To Have An Ear For Face Super-Resolution

A framework for multi-step probabilistic time-series/demand forecasting models

Code for paper "Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs"