short-paper

The VIA Annotation Software for Images, Audio and Video

Authors:

Abhishek Dutta,

Andrew ZissermanAuthors Info & Claims

MM '19: Proceedings of the 27th ACM International Conference on Multimedia

Pages 2276 - 2279

https://doi.org/10.1145/3343031.3350535

Published: 15 October 2019 Publication History

Abstract

In this paper, we introduce a simple and standalone manual annotation tool for images, audio and video: the VGG Image Annotator (VIA). This is a light weight, standalone and offline software package that does not require any installation or setup and runs solely in a web browser. The VIA software allows human annotators to define and describe spatial regions in images or video frames, and temporal segments in audio or video. These manual annotations can be exported to plain text data formats such as JSON and CSV and therefore are amenable to further processing by other software tools. VIA also supports collaborative annotation of a large dataset by a group of human annotators. The BSD open source license of this software allows it to be used in any academic project or commercial application.

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Information

Published In

cover image ACM Conferences

MM '19: Proceedings of the 27th ACM International Conference on Multimedia

October 2019

2794 pages

ISBN:9781450368896

DOI:10.1145/3343031

General Chairs:
Laurent Amsaleg
CNRS-IRISA, France
,
Benoit Huet
EURECOM, France
,
Martha Larson
Radboud University and TU Delft (Netherlands)
,
Program Chairs:
Guillaume Gravier
CNRS-IRISA, France
,
Hayley Hung
Delft University of Technology Netherlands
,
Chong-Wah Ngo
City University of Hong Kong Hong Kong
,
Wei Tsang Ooi
National University of Singapore Singapore

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 15 October 2019

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The Engineering and Physical Sciences Research Council (EPSRC)

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MM '19

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SIGMM

MM '19: The 27th ACM International Conference on Multimedia

October 21 - 25, 2019

Nice, France

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MM '19 Paper Acceptance Rate 252 of 936 submissions, 27%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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https://doi.org/10.26786/1920-7603(2025)778
Kumar AKumar PMahto MSrivastava S(2025)Breast Cancer Detection and Localization Using a Novel Multimodal ApproachIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2024.350288374(1-13)Online publication date: 2025
https://doi.org/10.1109/TIM.2024.3502883
Loewenstern YBenaroya-Milshtein NBelelovsky KBar-Gad I(2025)Automatic Identification of Facial Tics Using Selfie-VideoIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2024.348828529:1(409-419)Online publication date: Jan-2025
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Bhujel AWang YLu YMorris DDangol M(2025)A systematic survey of public computer vision datasets for precision livestock farmingComputers and Electronics in Agriculture10.1016/j.compag.2024.109718229(109718)Online publication date: Feb-2025
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