80 datasets found

Skeleton-based action recognition has attracted considerable attention due to its compact representation of the human body’s skeletal structure. Many recent methods have...

Skeleton-based action recognition has attracted considerable attention due to its compact representation of the human body’s skeletal structure. Many recent methods have...

The MSRAction3D dataset contains 567 Kinect depth map sequences from 10 people with 20 actions.

The 50 Salads dataset contains over 4.5 hours of video captures of different actors preparing 2 kinds of mixed salads (with 25 videos for each type of salad). While similar in...

The INRIA YouTube Instructional Videos dataset contains five tasks of different instructional domains: “making coffee”, “changing a car tire”, “CPR”, “jumping a car”, and...

The dataset used in the paper is a dataset of instructional videos, which includes 150 videos depicting 5 daily tasks, with an average of 9.5 actions per video.

The dataset used in the paper is a dataset of instructional videos, which includes 2,750 videos spanning 18 different tasks, with an average of 7.6 actions per video.

The dataset used in the paper is a large-scale instructional video dataset, which includes 11,827 videos involving 180 different tasks, with an average of 3.6 actions per video.

The KTH dataset consists of videos of 25 people performing different activities.

The Moments in Time dataset is a large-scale video action recognition dataset.

A dataset for action recognition, using spatio-temporal features.

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.

The Jester dataset is of continuous jokes ratings from -10 to 10, containing the jokes’ texts.

CMU Mocap dataset contains motion data of humans performing various actions such as running, walking, and jumping.

The Penn action dataset is a collection of videos of human actions performed by different people with different variations.

The dataset used for action recognition and retrieval of walking sequences based on appearance attributes.

Video classification is a fundamental problem in many video-based tasks. Applications such as autonomous driving technology, controlling drones and robots are driving the demand...

A video dataset for action recognition, consisting of 920 videos of 21 different actions.