24 datasets found

A large-scale video benchmark for human action recognition.

The ActivityNet1.2 dataset is a large-scale benchmark for action recognition and localization in videos.

THUMOS Challenge: Action Recognition with a Large Number of Classes.

Generating human action proposals in untrimmed videos is an important yet challenging task with wide applications. Current methods often suffer from the noisy boundary locations...

Temporal action proposal generation is an important task, akin to object proposals, temporal action proposals are intended to capture “clips” or temporal intervals in videos...

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

The Every Moment Counts dataset contains 1,000 hours of video footage of various activities.

The Hollywood in Homes dataset contains 9,848 videos of daily activities across 157 classes.

The THUMOS Challenge dataset contains 413 sports videos of 65 classes.

Propose an action recognition framework using Generative Adversarial Networks. Our model involves training a deep convolutional generative adversarial network (DCGAN) using a...

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.

The MUSES dataset is a collection of 3,697 videos, with 2,587 for training and 1,110 for testing.

Temporal action localization (TAL) is a prevailing task due to its great application potential. Existing works in this field mainly suffer from two weaknesses: (1) They often...

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

FineGym is a hierarchical video dataset for fine-grained action understanding, containing 354 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....

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...

Kinetics-700 is a large-scale video dataset for human action recognition, with 700 action categories.