Opendata, web and dolomites


Understanding Videos Automatically with the SensifAI Deep Learning Technology

Total Cost €


EC-Contrib. €






 SensifAI project word cloud

Explore the words cloud of the SensifAI project. It provides you a very rough idea of what is the project "SensifAI" about.

deep    internet    recognize    data    minute    describing    similarly    01    sport    unsafe    speech    objects    customized    founded    manually    80    tag    pricing    texts    million    involvement    landmarks    zurich    follow    contents    imaging    managed    believe    recognizes    recognition    google    sensifai    celebrities       tags    ranging    environment    searchable    learning    05    logos    marketplace    mobile    smartphones    accumulative    audio    starting    description    millions    aurally    audios    automated    semantic    visual    visually    wearable    cutting    eth    landmark    camera    became    captured    edge    equipped    accurately    contextual    international    videos    extremely    moods    images    scenes    automatically    genre    model    trained    microphone    scientists    leuven    traffic    oem    music    emerge    scene    people    impaired    ku    bvba    119    software    helping    day    content    web    recognizing    actions    alumni    europeans    trillion    amazon    action    surrounding    acquired    limited    cloud    delivers    tagging    emotion    video    mit    services    imagine   

Project "SensifAI" data sheet

The following table provides information about the project.


Organization address
address: DREVE DE NIVELLES 182/9
postcode: 1160
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Belgium [BE]
 Project website
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-1
 Funding Scheme SME-1
 Starting year 2018
 Duration (year-month-day) from 2018-12-01   to  2019-05-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    SENSIFAI BE (BRUSSELS) coordinator 50˙000.00


 Project objective

Google has a value of $1 trillion because it has managed to make texts searchable. However, 80% of internet traffic is videos, audios and images and they are not searchable. Making videos searchable is extremely challenging. This is why most of the video tagging is done manually and the results in automated video recognition are still limited. Mobile video recognition is also starting to emerge. SensifAI has developed a cutting-edge audio-visual deep-learning technology trained on millions of videos to recognize audio and video content and to tag them accurately. SensifAI automatically tags videos, images and audio, which makes them searchable and can be customized for a range of use cases. We believe our approach to contextual video analysis is unique and on the leading edge as it recognizes, scenes, actions, celebrities, landmarks, logos, music genre, moods and emotion and speech. SensifAI delivers the video recognition technology on the cloud on the Amazon Web Services Marketplace and can be embedded on devices such as smartphones (by OEM’s). Our software just became available on the Amazon Web Services Marketplace where we follow a unit-based pricing model ranging from €0.01/minute for recognizing landmark images/objects/celebrities/unsafe contents to €0.05/minute for general tagging and action/sport recognition. SensifAI bvba was founded by three alumni and scientists from MIT, ETH Zurich and KU Leuven, who acquired an accumulative experience in audio-visual data processing through involvement in many international projects. Imagine a day when the 30 million visually impaired Europeans use a wearable camera equipped with a software describing them the surrounding environment automatically by recognizing the semantic concept of the captured video. includes the description of the scene, objects, and activities. Similarly, imaging a technology when the 119 million aurally impaired people use a wearable microphone equipped with a software helping them.

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The information about "SENSIFAI" are provided by the European Opendata Portal: CORDIS opendata.

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