{"id":40896540,"url":"https://github.com/cschell/versatile-xr-user-identification","last_synced_at":"2026-01-22T02:23:58.801Z","repository":{"id":270126978,"uuid":"909339586","full_name":"cschell/Versatile-XR-User-Identification","owner":"cschell","description":"Implementation of \"Versatile User Identification in Extended Reality Using Pretrained Similarity-Learning\". 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The models are trained on data from players of \"Half-Life: Alyx\" and demonstrate:\n\n- Ability to identify new users from non-specific movements with minimal enrollment data\n- Fast new user enrollment (seconds vs days for retraining traditional classifiers) \n- More reliable performance with limited enrollment data\n- Cross-dataset generalization to different VR devices\n\n## Repository Structure\n\nThe codebase is organized into `data_preparation` and `machine_learning`. You find in each folder the corresponding Readmes.\n\n## Citation\n\nIf you use this code in your research, please cite:\n\n```bibtex\n@online{RackVersatileUserIdentification2023,\n  title = {Versatile {{User Identification}} in {{Extended Reality}} Using {{Pretrained Similarity-Learning}}},\n  author = {Rack, Christian and Kobs, Konstantin and Fernando, Tamara and Hotho, Andreas and Latoschik, Marc Erich},\n  date = {2023-07-03},\n  eprint = {2302.07517},\n  eprinttype = {arXiv},\n  doi = {10.48550/arXiv.2302.07517}\n}\n```\n\n## License\n\nThis work by Christian Rack, Konstantin Kob, Tamara Fernando, Andreas Hotho and Marc E. Latoschik is licensed under CC BY-NC-SA 4.0.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcschell%2Fversatile-xr-user-identification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcschell%2Fversatile-xr-user-identification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcschell%2Fversatile-xr-user-identification/lists"}