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WHO AM I?
WHO AM I?
I am an Assistant Professor in Computer Vision and Data Analysis at the University of Liège (ULiège), Belgium, where I founded the Vision and Information Understanding Laboratory (VIULab). I hold a degree in Electrical Engineering (2017) and completed my PhD in Computer Vision and AI at ULiège with support from the FNRS. During my postdoctoral research, I was a visiting researcher at King Abdullah University of Science and Technology (KAUST), working under the supervision of Prof. Marc Van Droogenbroeck and Prof. Bernard Ghanem.
My research focuses on advancing artificial intelligence for computer vision and video analysis. I explore a range of topics including perception on high-dimensional data, long-form video understanding, memory-augmented video neural networks, multimodal data fusion, and generative AI. These approaches are applied across various domains such as remote sensing, autonomous driving, and, most prominently, sports. I also co-organize international challenges on AI in sports through the SoccerNet platform, and regularly publish research on this topic.
To further promote our work and make it more accessible, I co-created a YouTube Channel with Adrien Deliège and Silvio Giancola, where we share insights and results from our research in computer vision.
NEWS
NEWS
[03-25] I started working as an Assistant Professor in Computer Vision and Data Analysis at the University of Liège (ULiège).
[02-24] Our SoccerNet 2024 Challenges are out! Check out our presentation video for details!
[05-23] Our SoccerNet story is featured on this great KAUST Insights News Article.
[02-23] I gave a talk about SoccerNet at the Bahrain Sport Summit.
[01-23] The Soccernet 2023 Challenges are out! Check out our presentation video for details.
[06-22] Received the Best Paper Award at the CVSports workshop!
[01-22] The Soccernet 2022 Challenges are out! Check out our presentation video for details.
Latest YouTube Videos
Latest YouTube Videos
SoccerNet 2024: Return of the Challenges!
SoccerNet 2024: Return of the Challenges!
Join the SoccerNet community and take part in the 2024 challenges in soccer video analysis. Be part of the research community pushing the boundaries of broadcast, field, and player understanding. With new tasks and challenges, including fine-grained ball action spotting, dense video captioning, multi-view foul recognition, and game state reconstruction, there's a challenge for everyone. With prizes for each challenge and a chance to be recognized at CVPR, start your journey now and help shape the future of soccer video analysis. Join our Discord community, follow us on social media, and be sure to leave a like and subscribe to our channel for updates. Let's get started!
Be the Champion of Soccer AI: Join the SoccerNet 2023 Challenges Now!
Be the Champion of Soccer AI: Join the SoccerNet 2023 Challenges Now!
Join the SoccerNet community and take part in the 2023 challenges in soccer video analysis. Be part of the research community pushing the boundaries of broadcast, field, and player understanding. With new tasks and challenges, including fine-grained action spotting, dense video captioning, and jersey number recognition, there's a challenge for everyone. With prizes for each challenge and a chance to be recognized at CVPR, start your journey now and help shape the future of soccer video analysis. Join our Discord community, follow us on social media, and be sure to leave a like and subscribe to our channel for updates. Let's get started!
Soccer Player Tracking, Re-ID, Camera Calibration and Action Spotting - SoccerNet Challenges 2022
Soccer Player Tracking, Re-ID, Camera Calibration and Action Spotting - SoccerNet Challenges 2022
In this video, we present our new SoccerNet Challenges for CVPR 2022! We introduce the three tasks of Calibration, Re-identification and Tracking on soccer games, in partnership with EVS Broadcast Equipment, SportRadar and Baidu Research. We also reiterate our previous Action Spotting and Replay Grounding Challenges at the ActivityNet workshop. Good luck fighting for the throne!
Camera Calibration and Player Localization in SoccerNet-v2
Camera Calibration and Player Localization in SoccerNet-v2
In this video, we present our paper: “Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spotting” published at the CVPR 2021 workshop CVsports. This work introduces a camera calibration and player localization algorithm for the SoccerNet-v2 dataset. Next, a method based on CALF is proposed to investigate different types of representations of this player localization for the task of action spotting.
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