I am currently working as a Ph. D. Student in the team of Prof. Marc Van Droogenbroeck. I am developing novel computer vision and deep learning based techniques for the problem of automatic video understanding and analysis in the context of sports videos.
Ph.D. Student in Computer Vision and Deep Learning at the University of Liège (ULiège), Belgium. Research centered on semantic segmentation and global video understanding in the case of sports videos. Financed by a four-year FRIA research grant (FRS - FNRS).
Master’s degree in Eletrical Engineering specialized in Telecommunications and Signal Processing at ULiège.
Bachelor’s degree in Civil Engineering at ULiège with Electricity and Physics as options.
I am currently working as a Ph. D. candidate in the laboratory of Prof. Van Droogenbroeck. I am developing computer vision and deep learning-based techniques for the problem of automatic video understanding and analysis in the context of sports videos. Recently, I have been working on a novel method which allows to produce real-time segmentation masks of the soccer players in a video sequences using a deep learning network that adapts to the latest game conditions by continuously learning new features during the match (named ARTHuS, best paper award at CVPR 2019’s CVsports workshop). I coordinated this project with researchers from the University of Louvain. I also participated in the study of capsule networks and how they can be used to interpret the features captured by the layers (named HitNet, accepted at AAAI 2019’s workshop on network interpretability). Prior to these works, I worked on a bottom-up approach for classifying game events in soccer videos using low level features extracted with techniques that I developed. This paper won the best paper award at CVPR 2018’s workshop CVsports. At the moment, I am working on the integration of semantic information to improve the performances of background subtraction algorithms.
University of Liège
10 Allée de la découverte
Tel. +32 4 366 26 41