Aff-Wild2 database

Affective computing has been largely limited in terms of available data resources. The need to collect and annotate diverse in-the-wild datasets has become apparent with the rise of deep learning models, as the default approach to address any computer vision task.
Some in-the-wild databases have been recently proposed. However: i) their size is small, ii) they are not audiovisual, iii) only a small part is manually annotated, iv) they contain a small number of subjects, or v) they are not annotated for all main behavior tasks (valence arousal estimation, action unit detection and basic expression classification).
To address these, we substantially extend the largest available in-the-wild database (Aff-Wild) to study continuous emotions such as valence and arousal. Furthermore, we annotate parts of the database with basic expressions and action units. We call this database Aff-Wild2. To the best of our knowledge, AffWild2 is the only in-the-wild database containing annotations for all 3 main behavior tasks. The database is also a large scale one. It is also the first audiovisual database with annotations for AUs. All AU annotated databases do not contain audio, but only images or videos.

The Aff-Wild2 is annotated in a per frame basis for the seven basic expressions (i.e., happiness, surprise, anger, disgust, fear, sadness and the neutral state), twelve action units (AUs 1,2,4,6,7,10,12,15,23,24,25, 26) and valence and arousal. In total Aff-Wild2 consists of 564 videos of around 2.8M frames with 554 subjects (326 of which are male and 228 female). All videos have been annotated in terms of valence and arousal. 546 videos of around 2.6M frames have been annotated in terms of the basic expressions. 541 videos of around 2.6M frames have been annotated in terms of action units. Aff-Wild2 displayes a big diversity in terms of subjects' ages, ethnicities and nationalities; it has also great variations and diversities of environments.

How to acquire Aff-Wild2

If you are an academic, (i.e., a person with a permanent position at a research institute or university, e.g. a professor, but not a Post-Doc or a PhD/PG/UG student), please:
i) fill in this EULA;
ii) use your official academic email (as data cannot be released to personal emails);
iii) send an email to d.kollias@qmul.ac.uk with subject: Aff-Wild2 request by academic;
iv) include in the email the above signed EULA, the reason why you require access to the Aff-Wild2 database, and your official academic website

In the case of Post-Docs or Ph.D. students: your supervisor/advisor should perform the above described steps.

If you are from industry and you want to acquire Aff-Wild2, please send an email from your official industrial email to d.kollias@qmul.ac.uk with subject: Aff-Wild2 request from industry and explain the reason why the database access is needed; also specify if it is for research or commercial purposes.

If you are an undergraduate or postgraduate student (but not a Ph.D. student), please:
i) fill in this EULA; you must print and sign the EULA in ink; a wet signature is required; no electronic signature will be accepted
ii) use your official university email (data cannot be released to personal emails);
iii) send an email to d.kollias@qmul.ac.uk with subject: Aff-Wild2 request by student
iv) include in the email the above signed EULA and proof/verification of your current student status (eg student ID card).
To all UG/PG students: 
1 ) The database cannot be shared to students for research internships; the supervisor should instead follow the steps outlined in the two above cases (industry or academia).
2)  If the email does not contain all the required information or if the email contains incorrect information (e.g. non filled in EULA or non signed EULA or EULA not signed in ink or an incorrect EULA), then the database access request will be automatically rejected and there will be no reply to the request. 

Due to the high volume of requests, please allow about 14 days for the reply to your request for access.