Introduction: The dataset features 15 different classes of Human Activities. The dataset contains about 12k+ labelled images including the validation images ...

The dataset consists of around 500,000 video clips covering 600 human action classes with at least 600 video clips for each action class. Each video clip lasts ...

HACS is a dataset for human action recognition. It uses a taxonomy of 200 action classes, which is identical to that of the ActivityNet-v1.3 dataset. It has ...

We have a structured dataset split into train and test containing 15 classes each. The classes are calling, clapping, cycling, dancing, drinking, eating, ...

The dataset consists of approximately 300,000 video clips, and covers 400 human action classes with at least 400 video clips for each action class. Each clip ...

This project introduces a novel video dataset, named HACS (Human Action Clips and Segments). It consists of two kinds of manual annotations.

The dataset contains 27 actions performed by 8 subjects (4 females and 4 males). Each subject repeated each action 4 times. After removing three corrupted ...

---- A dataset for understanding human actions in still images. Introduction The Stanford 40 Action Dataset contains images of humans performing 40 actions.

27 июн. 2023 г. · We present the Human Action Dataset (HAD), a large-scale functional magnetic resonance imaging (fMRI) dataset for human action recognition.

25 февр. 2022 г. · Human action datasets are used within AI/ML models to help organizations understand real-time action and kinetic, organic movement.