30 datasets found

The Penn Action dataset is a real video dataset of people performing various indoor and outdoor sports with annotations of human joint locations.

UTD-MHAD dataset for human action recognition

The AID dataset is a benchmark for scene classification in remote sensing. It contains aerial images with 30 scene types.

Skeleton-based action recognition, which classifies human actions based on the coordinates of joints and their connectivity within skeleton data.

The SBU kinect dataset is an interaction dataset acquired using the Microsoft kinect sensor.

The Charades dataset is a dataset for human action recognition. It contains 200 videos with 3,800+ action instances.

The dataset used in this paper for Human Action Recognition tasks (HAR) using 3D Convolutional Neural Networks.

The dataset used in this paper for Human Action Recognition tasks (HAR) using 3D Convolutional Neural Networks.

A large-scale human action recognition dataset collected in indoor environments.

The HACS dataset contains 200 action classes with 504K videos.

The Epic-Kitchens-100 dataset contains 97 verb and 300 noun classes with actions defined by the combination of nouns and verbs.

The Something-Something-V1 and V2 dataset contains 174 human action categories with 108K and 220K videos.

The authors used the UCF101, HMDB51, and Diving48 datasets to evaluate the performance of their proposed algorithm.

The Kinetics dataset is a large-scale action recognition dataset. It contains videos of various actions performed by humans, with annotations of the actions performed.

UCF-101 dataset is a large-scale action recognition dataset, containing 13,320 videos categorized into 101 human action categories.

Human perception of surroundings is often guided by the various poses present within the environment. Many computer vision tasks, such as human action recognition and robot...

The dataset used in this paper is K400, a dataset for human action recognition.

The dataset used in this paper is SSv2, a dataset for human action recognition.

The Kinetics-600 dataset consists of 392k training videos and 30k validation videos in 600 human action categories.

The DHA database is orgnized with 483 depth video sequences for 23 actions.