Human Activity Recognition

78 papers with code • 0 benchmarks • 1 datasets

Classify various human activities


Use these libraries to find Human Activity Recognition models and implementations


Most implemented papers

Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors

guillaume-chevalier/HAR-stacked-residual-bidir-LSTMs 22 Aug 2017

Human activity recognition (HAR) has become a popular topic in research because of its wide application.

A Probabilistic Logic Programming Event Calculus

MarcRoigVilamala/DeepProbCEP 9 Apr 2012

The input of our system is a set of time-stamped short-term activities (STA) detected on video frames.

Kernel Cross-Correlator

wang-chen/KCC 12 Sep 2017

Cross-correlator plays a significant role in many visual perception tasks, such as object detection and tracking.

Understanding and Improving Deep Neural Network for Activity Recognition

manish-vi/Human-Activity-Recognition 18 May 2018

After that, we extracted the significant features related to the activities and sent the features to the DNN-based fusion model, which improved the classification rate to 96. 1%.

Human activity recognition from skeleton poses

frederico-klein/cad-gas 20 Aug 2019

Human Action Recognition is an important task of Human Robot Interaction as cooperation between robots and humans requires that artificial agents recognise complex cues from the environment.

Human Activity Recognition from Wearable Sensor Data Using Self-Attention

saif-mahmud/self-attention-HAR 17 Mar 2020

In this regard, the existing recurrent or convolutional or their hybrid models for activity recognition struggle to capture spatio-temporal context from the feature space of sensor reading sequence.

Sequential Weakly Labeled Multi-Activity Localization and Recognition on Wearable Sensors using Recurrent Attention Networks

KennCoder7/RAN 13 Apr 2020

Recently, several attention mechanisms are proposed to handle the weakly labeled human activity data, which do not require accurate data annotation.

DANA: Dimension-Adaptive Neural Architecture for Multivariate Sensor Data

mmalekzadeh/dana 5 Aug 2020

We introduce a dimension-adaptive pooling (DAP) layer that makes DNNs flexible and more robust to changes in sensor availability and in sampling rate.

A benchmark of data stream classification for human activity recognition on connected objects

azazel7/paper-benchmark 27 Aug 2020

We measure both classification performance and resource consumption (runtime, memory, and power) of five usual stream classification algorithms, implemented in a consistent library, and applied to two real human activity datasets and to three synthetic datasets.

B-HAR: an open-source baseline framework for in depth study of human activity recognition datasets and workflows

B-HAR-HumanActivityRecognition/B-HAR 23 Jan 2021

Human Activity Recognition (HAR), based on machine and deep learning algorithms is considered one of the most promising technologies to monitor professional and daily life activities for different categories of people (e. g., athletes, elderly, kids, employers) in order to provide a variety of services related, for example to well-being, empowering of technical performances, prevention of risky situation, and educational purposes.