human-activity-recognition

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

Time Series Feature Extraction Library (TSFEL): 60+ statistical, temporal, spectral and fractal features for time series classification, regression and signal processing in Python

Real-Time Spatio-Temporally Localized Activity Detection by Tracking Body Keypoints

Python implementation of KNN and DTW classification algorithm

[IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"

Convolutional Neural Network for Human Activity Recognition in Tensorflow

MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope) (PMC Journal) (IoTDI'19)

An up-to-date & curated list of Awesome IMU-based Human Activity Recognition(Ubiquitous Computing) papers, methods & resources. Please note that most of the collections of researches are mainly based on IMU data.

Unity's privacy-preserving human-centric synthetic data generator

Quickly add MediaPipe Pose Estimation and Detection to your iOS app. Enable powerful features in your app powered by the body or hand.

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

[TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

Always up-to-date, most comprehensive HAR resource — continuously scanned and auto-updated from Papers with Code. 53 datasets integrated across all modalities.

A collection of datasets, papers, and resources for Generalizable Human Activity Recognition and IMU sensing.

Human Activity Recognition based on WiFi Channel State Information

Multi Person Skeleton Based Action Recognition and Tracking

Abnormal Human Behaviors Detection/ Road Accident Detection From Surveillance Videos/ Real-World Anomaly Detection in Surveillance Videos/ C3D Feature Extraction

Self-supervised learning for wearables using the UK-Biobank (>700,000 person-days)

Human Activity Recognition using Channel State Information