18 datasets found

The UCF101-24 dataset is a subset of the UCF101 dataset, containing 3207 videos with spatio-temporal annotations on 24 action categories.

Person search unifies person detection and person re-identification (Re-ID) to locate query persons from the panoramic gallery images. One major challenge comes from the...

A large-scale face-aging database for automated face age-progression and age estimation in both images and videos.

The UMN dataset consists of three different crowd scenes, and the dataset has 11 videos from these scenes, with a resolution of 240 × 320. Each video sequence represents a...

The Sports-1M dataset is a large-scale video dataset for activity recognition. It contains 600 classes of actions, with 50 hours of video footage.

The CelebV-HQ dataset contains 35,666 face videos from over 15,000 identities.

The Harmonic dataset is a collection of 4K videos.

The dataset used in the LORD framework for autonomous driving, consisting of images, videos, and text-based observations.

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

The Kinetics dataset is a large-scale video dataset for human action recognition.

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 AVA-Kinetics dataset is a video dataset of localized human actions.

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...

The dataset used in this paper is a Flickr image dataset, which is used to evaluate the proposed deep aesthetic feature learning framework.

The dataset used in this paper is a collection of videos for various tasks such as video recognition and action recognition.

Temporal activity detection has drawn increasing interests in both academic and industry communities due to its vast potential applications in security surveillance, behavior...