CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Deliverables
By adding new games to our pipeline we are able to offer richer quests and challenges experiences
Challenge feed recommendation system (opens in new window)Our existing RecSys project is reconverted and improved to support quests and challenges engagement
Wallet supports the 3 major blockchains (opens in new window)Continuous effort of adding multiple blockchains / wallets supported
PC configurations management (opens in new window)PC configurations management (continuous)
Integration of 30 detection models on PC (opens in new window)PC app supports 30 detection models
Integration of 20 detection models on PC (opens in new window)Integration of 20 AI detection models to our PC app
Onboarding discovery (opens in new window)The user experience of quests and challenges is optimised on mobile
Setting up a process for prototype testing (opens in new window)Industrialising our prototype testing
Continuous improvements on PC video recorder CPU & GPU usage (opens in new window)Reduce CPU GPU usage on the users devices
Production launch and nominal operation on PC (opens in new window)Crypto wallet is launched on our PC app at nominal operations
Digital assets marketplace test release (opens in new window)In-app test release
Partners due diligence and selection (Crypto wallet) (opens in new window)We identify audit and select one or multiple crypto wallet partners
Leaderboard launch (opens in new window)A leaderboard where users can see their ranking compared to other participants to quests and challenges is relased
Integration of 15 detection models on PC (opens in new window)PC app supports 15 detection models
Security and implementation testing (opens in new window)Security is critical when handling users assets
Reaching 80% fidelity in new models detection (opens in new window)Reaching high levels of fidelity in the new games added to the model
Improvement on the delays to create an integrate new models for new games (opens in new window)In the perspective of scaling our user base, scaling our approach becomes critical
Optimisation of video resolution (opens in new window)Optimisation of video resolution for external sharing
Redesign of the user profile to highlight rewards PC (opens in new window)Redesign of the user profile to highlight rewards user library
Guaranteeing efficient R&D activities (opens in new window)Ensuring an high level view of all R&D activities all along the project timeline
Redesign of the user profile to highlight rewards Mobile (opens in new window)The user profile is redesigned fully to offer a consistent and enjoyable app experience
Reduce crash rate (opens in new window)reduce the crash rate to 5 to offer a seamless experience
Digital assets marketplace product release (opens in new window)Product release in the public app
Set up of automatic bots to share clips, achievements, etc. with other users (opens in new window)Distribution set up of automatic bots to share clips achievements etc with other users
"PhD research thesis ""Analysis of human behavior from video games using deep learning approaches"" (due in 36 months)"
Crypto wallet is launched on our mobile app at nominal operations
Quests launch on mobile thanks to the mobile recorder rebuild (opens in new window)Quests individual challenges are released on mobile
Reach 100k Discord users on Powder servers / using the Powder discord bot
Publications
Author(s):
Liam Schoneveld, Alice Othmani, Hazem Abdelkawy
Published in:
Pattern Recognition Letters, 2021, ISSN 0167-8655
Publisher:
Elsevier
DOI:
10.1016/j.patrec.2021.03.007
Author(s):
H. Terbouche, L. Schoneveld, O. Benson, A. Othmani
Published in:
IEEE Access, Issue Volume 10, pp. 41622-41638, 2022, ISSN 2169-3536
Publisher:
IEEE Access
DOI:
10.1109/ACCESS.2022.3164745
Author(s):
L. Schoneveld, A. Othmani
Published in:
2021 IEEE International Conference on Image Processing (ICIP), Issue 2339-2342, 2021, ISSN 2381-8549
Publisher:
IEEE Computer Society
DOI:
10.1109/ICIP42928.2021.9506025
Author(s):
Hacene Terbouche, Maryan Morel, Mariano Rodriguez, Alice Othmani
Published in:
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023, ISSN 3142-3151
Publisher:
IEEE/CVF (Computer Vision Foundation)
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