Activity Recognition

246 papers with code • 4 benchmarks • 29 datasets

Human Activity Recognition is the problem of identifying events performed by humans given a video input. It is formulated as a binary (or multiclass) classification problem of outputting activity class labels. Activity Recognition is an important problem with many societal applications including smart surveillance, video search/retrieval, intelligent robots, and other monitoring systems.

Source: Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters

Libraries

Use these libraries to find Activity Recognition models and implementations

Latest papers with no code

Machine Learning Techniques for Sensor-based Human Activity Recognition with Data Heterogeneity -- A Review

no code yet • 12 Mar 2024

Sensor-based Human Activity Recognition (HAR) is crucial in ubiquitous computing, analysing behaviours through multi-dimensional observations.

ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Models

no code yet • 11 Mar 2024

Neuro-Symbolic AI (NeSy) provides an interesting research direction to mitigate this issue, by infusing common-sense knowledge about human activities and the contexts in which they can be performed into HAR deep learning classifiers.

FocusCLIP: Multimodal Subject-Level Guidance for Zero-Shot Transfer in Human-Centric Tasks

no code yet • 11 Mar 2024

We propose FocusCLIP, integrating subject-level guidance--a specialized mechanism for target-specific supervision--into the CLIP framework for improved zero-shot transfer on human-centric tasks.

A Survey of Application of Machine Learning in Wireless Indoor Positioning Systems

no code yet • 7 Mar 2024

Numerous attempts have been made in the literature to develop efficient indoor positioning systems (IPSs), with a growing focus on machine learning (ML) based techniques.

HARGPT: Are LLMs Zero-Shot Human Activity Recognizers?

no code yet • 5 Mar 2024

Our study, HARGPT, presents an affirmative answer by demonstrating that LLMs can comprehend raw IMU data and perform HAR tasks in a zero-shot manner, with only appropriate prompts.

Human Activity Recognition with Low-Resolution Infrared Array Sensor Using Semi-supervised Cross-domain Neural Networks for Indoor Environment

no code yet • 5 Mar 2024

The label classifier obtained from training the source domain data improves the recognition of target domain activities due to the semi-supervised learning utilized in training the target domain data.

Fast Low-parameter Video Activity Localization in Collaborative Learning Environments

no code yet • 2 Mar 2024

Research on video activity detection has primarily focused on identifying well-defined human activities in short video segments.

MaskFi: Unsupervised Learning of WiFi and Vision Representations for Multimodal Human Activity Recognition

no code yet • 29 Feb 2024

Benefiting from our unsupervised learning procedure, the network requires only a small amount of annotated data for finetuning and can adapt to the new environment with better performance.

Comparative Analysis of XGBoost and Minirocket Algortihms for Human Activity Recognition

no code yet • 28 Feb 2024

This study investigates the efficacy of two ML algorithms, eXtreme Gradient Boosting (XGBoost) and MiniRocket, in the realm of HAR using data collected from smartphone sensors.

RISAR: RIS-assisted Human Activity Recognition with Commercial Wi-Fi Devices

no code yet • 27 Feb 2024

Human activity recognition (HAR) holds significant importance in smart homes, security, and healthcare.