A Short Note about Kinetics-600

TL;DR

This paper details the extension of the Kinetics-600 dataset from 400 to 600 classes, increasing data volume and diversity through multilingual queries, and provides baseline results using I3D architecture.

Contribution

It introduces a larger, more diverse version of the Kinetics dataset with new data collection methods and baseline benchmarks.

Findings

Expanded dataset to 600 classes with at least 600 clips each

Implemented multilingual data collection process

Provided baseline results with I3D neural network

Abstract

We describe an extension of the DeepMind Kinetics human action dataset from 400 classes, each with at least 400 video clips, to 600 classes, each with at least 600 video clips. In order to scale up the dataset we changed the data collection process so it uses multiple queries per class, with some of them in a language other than english -- portuguese. This paper details the changes between the two versions of the dataset and includes a comprehensive set of statistics of the new version as well as baseline results using the I3D neural network architecture. The paper is a companion to the release of the ground truth labels for the public test set.