Giter Site home page Giter Site logo

sqiangcao99 / ava-dataset Goto Github PK

View Code? Open in Web Editor NEW

This project forked from cvdfoundation/ava-dataset

0.0 0.0 0.0 10 KB

The AVA dataset densely annotates 80 atomic visual actions in 351k movie clips with actions localized in space and time, resulting in 1.65M action labels with multiple labels per human occurring frequently.

ava-dataset's Introduction

AVA Actions Dataset

The AVA dataset densely annotates 80 atomic visual actions in 430 movie clips with actions localized in space and time, resulting in 1.62M action labels with multiple labels per human occurring frequently. Clips are drawn from 15-minute contiguous segments of movies, to open the door for temporal reasoning about activities. The dataset is split into 235 videos for training, 64 videos for validation, and 131 videos for test. This page aims to provide the download instructions and mirror sites for AVA Dataset. Please visit the project page for more details on the dataset.

Download Videos

CVDF hosts the videos in the AVA dataset. Please download the videos with the url patterns:

https://s3.amazonaws.com/ava-dataset/trainval/[file_name]
https://s3.amazonaws.com/ava-dataset/test/[file_name]

You can download the list of training/validation file names here, and the test filenames here.

Download Annotations

The public annotations, for the training and validation sets, can be downloaded here ava_v2.2.zip.

AVA ActiveSpeaker Dataset

AVA ActiveSpeaker associates speaking activity with a visible face, on the AVA v1.0 videos, resulting in 3.65 million frames labeled across ~39K face tracks. A detailed description of this dataset is in the arXiv paper.

Download Videos

CVDF hosts the videos in AVA ActiveSpeaker. Please download the videos with the url patterns:

https://s3.amazonaws.com/ava-dataset/trainval/[file_name]

You can download the list of file names here.

Download Annotations

The public annotations for AVA ActiveSpeaker can be downloaded here ava_activespeaker_train_v1.0.tar.bz2 and ava_activespeaker_val_v1.0.tar.bz2.

AVA Speech Dataset

The AVA-Speech dataset densely annotates speech activity for the movie clips in the AVA v1.0 dataset. It explicitly labels 3 background noise conditions (Clean Speech, Speech with background Music, and Speech with background Noise), resulting in ~40K labeled segments spanning 40 hours of data. Please visit the project page for more details on the dataset.

Download Videos

CVDF hosts the videos in AVA Speech. Please download the videos with the url patterns:

https://s3.amazonaws.com/ava-dataset/trainval/[file_name]

You can download the list of file names here.

Download Annotations

The public annotations for AVA speech can be downloaded here ava_speech_labels_v1.csv.

ava-dataset's People

Contributors

raviddoss avatar tylin avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.