12 datasets found

YouTube-8M is a large-scale video classification benchmark.

The VideoLT dataset contains 1,004 classes and about 256,218 untrimmed videos collected from YouTube, covering a wide range of human activities, including everyday life,...

Towards long-form video understanding. We propose a two-stream spatio-temporal attention network for long video classification which combines the advantages of convolutional...

The dataset used in this paper is a benchmark dataset for image and video classification. It contains 15 scenes with 4485 images, and 102 classes with 9144 images. The dataset...

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 dataset used for text-to-video retrieval and video classification tasks.

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.

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

The ActivityNet Captions is a benchmark dataset proposed for dense video captioning. There are 20K untrimmed videos in total, and each video has several annotated segments with...

The dataset used in the paper is MSR-VTT, a large video description dataset for bridging video and language. The dataset contains 10k video clips with length varying from 10 to...

Youtube-8M is a large-scale video classification benchmark.

The dataset used for video action classification, consisting of 9.8k training videos, 1.8k validation videos, and 157 classes.