A Detailed Framework for Semantic Description of Humans 

Semantic description of humans in images and videos is one of the fundamental problems in computer vision with many applications such as visual surveillance, facial verification, health care, image and video search engines, tagging suggestions and human-computer interaction.

Computer visionHumans in different shapes.Humans have an outstanding ability when it comes to recognizing (i) semantic attributes such as age, gender, hair style and clothing style (ii) actions such as riding a horse, climbing, running and walking and (iii) facial expressions such as angry, happy and smiling.

We are currently developing novel deep learning solutions for the challenging problem of semantic description of humans in images and videos. The major emphasis is to investigate the challenging generic sub-problems of efficient image and video description, automatic learning of visual models, joint learning from textual annotations and visual data and learning robust methods with minimal supervision.

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A selection of three publications

Fahad Khan, Joost van de Weijer, Rao Muhammad Anwer, Andrew D. Bagdanov, Michael Felsberg, Jorma Laaksonen (2018)

Machine Vision and Applications , Vol.29 , s.55-71 Continue to DOI

Fahad Khan, Jiaolong Xu, Joost van de Weijer, Andrew D. Bagdanov, Rao Muhammad Anwer, Antonio M. Lopez (2015)

IEEE Transactions on Image Processing , Vol.24 , s.4422-4432 Continue to DOI

Rao Muhammad Anwer, Fahad Khan, Jorma Laaksonen (2018)

2018 INTERNATIONAL CONFERENCE ON BIOMETRICS (ICB) , s.90-97 Continue to DOI

WASP research at CVLShow/Hide content