8 datasets found

The dataset used in the paper is HMDB51 and UCF101.

The dataset used in the paper is Kinetics-400 and Something-Something-V2.

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

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....

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.