Real-Time Spatio-Temporally Localized Activity Detection by Tracking Body Keypoints
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Updated
Sep 23, 2023 - Python
Real-Time Spatio-Temporally Localized Activity Detection by Tracking Body Keypoints
deep learning sex position classifier
This repository allows you to classify 40 different human actions. Pose detection, estimation and classification is also performed. Poses are classified into sitting, upright and lying down.
Keras implementation of Human Action Recognition for the data set State Farm Distracted Driver Detection (Kaggle)
Source code for "Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching", AAAI2020
Surveillance Perspective Human Action Recognition Dataset: 7759 Videos from 14 Action Classes, aggregated from multiple sources, all cropped spatio-temporally and filmed from a surveillance-camera like position.
This repository contains the MPOSE2021 Dataset for short-time pose-based Human Action Recognition (HAR).
[AAAI-2024] HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors
This repository provides implementation of a baseline method and our proposed methods for efficient Skeleton-based Human Action Recognition.
Human Activity Recognition Research Repository
Code for HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data, IEEE PerCom CoMoRea 2022
A skeleton-based real-time online action recognition project, classifying and recognizing base on framewise joints, which can be used for safety surveilence.
Implementation of some popular skeleton based Human Action Recognition methods basis on Deep Neural Networks.
A human action dataset collected from Elder Scrolls V: Skyrim
Source code of experiments performed in paper: Human Action Recognition in Videos Based on Spatiotemporal Features and Bag-of-Poses
This python opencv code is used to segment the human object from the video frame
[ECCV 2024]Temporary code for "Ad-HGformer: An Adaptive HyperGraph Transformer for Skeletal Action Recognition"
Implementation of CNN-Based Model for Online Action Recognition
This is an effort to provide different approaches towards human action recognition from video. A method to perform data augmentation on skeletal data so as to achieve a view independent recognition approach is included.
Thesis, Video Based Human Action Recognition Using Deep Learning
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