Omkar2118/datasets huggingface dataset:
Kinetics-600

The **Kinetics-600** is a large-scale action recognition dataset which consists of around 480K videos from 600 action categories. The 480K videos are divided into 390K, 30K, 60K for training, validation and test sets, respectively. Each video in the dataset is a 10-second clip of action moment annotated from raw YouTube video. It is an extensions of the Kinetics-400 dataset.

Source: [Learning to Localize Actions from Moments](https://arxiv.org/abs/2008.13705)
Image Source: [https://towardsdatascience.com/downloading-the-kinetics-dataset-for-human-action-recognition-in-deep-learning-500c3d50f776](https://towardsdatascience.com/downloading-the-kinetics-dataset-for-human-action-recognition-in-deep-learning-500c3d50f776)

Introducing paper: A Short Note about Kinetics-600
AudioSet

Audioset is an audio event dataset, which consists of over 2M human-annotated 10-second video clips. These clips are collected from YouTube, therefore many of which are in poor-quality and contain multiple sound-sources. A hierarchical ontology of 632 event classes is employed to annotate these data, which means that the same sound could be annotated as different labels. For example, the sound of barking is annotated as Animal, Pets, and Dog. All the videos are split into Evaluation/Balanced-Train/Unbalanced-Train set.

Source: [Curriculum Audiovisual Learning](https://arxiv.org/abs/2001.09414)

Introducing paper: Audio Set: An ontology and human-labeled dataset for audio events