10 datasets found

This dataset is used for action localization tasks.

The KTH action dataset consists of humans performing 6 types of actions: boxing, clapping, waving, jogging, running, and walking under 4 scenarios: outdoors, outdoors with scale...

The Stanford40 and HII datasets are used for image recognition. The Stanford40 dataset contains 40 action categories, while the HII dataset contains 10 action images.

The UCF101 and HMDB51 datasets are used for video recognition. The UCF101 dataset contains 101 action categories, while the HMDB51 dataset contains 51 classes.

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 dataset of real videos for action categorization, including HMDB-51 and UCF-101.

Motion has shown to be useful for video understanding, where motion is typically represented by optical flow. However, computing flow from video frames is very time-consuming....

The UCF101 dataset contains 13320 videos distributed in 101 action categories. This dataset is different from the above ones in that it contains mostly coarse sports activities...

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...

The Kinetics dataset is a large-scale human action dataset, which consists of 400 action classes where each category has more than 400 videos.