Slawomir Tadeja

A paper accepted at NeurIPS 2024

A paper co-authored by Dr Sławomir Tadeja from the CHL has been accepted for inclusion at the prestigious 2024 Conference on Neural Information Processing Systems (NeurIPS 2024): J. Waczyńska, P. Borycki, J. Kaleta,  S. Tadeja, P. Spurek, D-MiSo:  Editing Dynamic 3D Scenes using Multi-Gaussians Soup,  The 2024 Neural Information Processing Systems (NeurIPS 2024), (accepted)

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AR for exoskeleton fitting presented at the ongoing IEEE RAS/EMBS BioRob 2024

Christine Saeedi-Givi is presenting her first-author paper at the 10th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2024): Exergame-Like Feedback for Passive Upper Limbs Exoskeleton Fitting: A Feasibility Study with Augmented Reality Author(s): Christine Saeedi-Givi, Lennard Schwaab, Thomas Bohné, Slawomir Konrad Tadeja Christine will return to CHL this upcoming term to conduct research

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A paper and a poster accepted at the inaugural 2024 IEEE International Symposium on Emerging Metaverse (ISEMV)

We are pleased to announce that a paper co-authored by CHL members Dr S.K. Tadeja and Dr T. Bohné was accepted for presentation at the 2024 IEEE International Symposium on Emerging Metaverse (ISEMV) collocated with the IEEE ISMAR 2024 conference: S.K. Tadeja, A. Filipowski, M. Frankowski, M. Igras-Cybulska, T. Bohné, P.O. Kristensson, Utilising FAST Design

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Three workshop papers accepted at IEEE ISMAR-Adjunct 2024!

Three workshop papers co-authored by Dr Thomas Bohne and Dr Slawomir Tadeja, as well as former visiting student Alex Albers (currently PhD student at ETH), have been accepted for publication at IEEE ISMAR-Adjunct. Please find more details below. The MASK! Mobile Analytics from Situated Knowledge,​ Friday, October 25, 2024 K. Moskała, M. Frankowski, M. Igras-Cybulska,

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A new journal article at MTAP

Based on sixteen domain expert interviews, we developed a tool to help prepare customised deployment strategies for AR-based assistance systems utilising manual assembly as the main example. Please find this article open access at this link: Bock, L., Bohné, T. & Tadeja, S.K. Decision support for augmented reality-based assistance systems deployment in industrial settings. Multimed Tools

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