Human Activity Detection with TensorFlow and Python.
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Updated
Apr 27, 2024 - Python
Human Activity Detection with TensorFlow and Python.
Human Pose Estimation for multi-view Human Action Recognition
Repository for the paper Accuracy Comparison of CNN, LSTM, and Transformer for Activity Recognition Using IMU and Visual Markers, containing all the datasets and Jupyter notebooks used for experiments
his is a human action recognition(HAR) project based on CNNs and Tensorflow using a pretrained model.
11000-Image-Video-caption-data-of-human-action
Human Action Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Hirakawa
專題分類動作的程式
Project to explore a deep learning solution to a computer vision problem. Human action recognition has become increasingly popular. This project implements a deep RNN to detect seizures.
This python opencv code is used to segment the human object from the video frame
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.
[ECCV 2024]Temporary code for "Ad-HGformer: An Adaptive HyperGraph Transformer for Skeletal Action Recognition"
Thesis, Video Based Human Action Recognition Using Deep Learning
2341-People-Human-Action-Data-in-Online-Conference-Scenes
Striking the Balance: Human Pose Estimation based Optimal Fall Recognition
A system for Human Action Recognition that uses the scale and body orientation invariant Skeletal Quads representation, with an LSTM network
机器学习实现基于手机六轴数据的人体动作识别和计数功能。并利用云服务器和微信小程序在手机上实现。 Use machine learning to achieve human activity recognition and counting function based on cell phone six-axis data. Achieve it on phone using ECS and WeChat mini-program.
Source code of experiments performed in paper: Human Action Recognition in Videos Based on Spatiotemporal Features and Bag-of-Poses
Synthetically Generated Surveillance Perspective Human Action Recognition Dataset: 6901 Videos from 10 action classes, made by a 3D Simulation, all cropped spatio-temporally and filmed from a surveillance-camera like position.
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