Tim Rolff

2023

• André Peter Kelm, Lucas Schmidt, Tim Rolff, Christian Wilms, Ehsan Yaghoubi, Simone Frintrop: High-Level Features Parallelization for Inference Cost Reduction Through Selective Attention, arXiv:2308.05128, 2023, [arXiv], [PDF]
• Tim Rolff, Susanne Schmidt, Frank Steinicke, Simone Frintrop: A Deep Learning Architecture for Egocentric Time-to-Saccade Prediction using Weibull Mixture-Models and Historic Priors, Symposium on Eye Tracking Research and Applications (ETRA ’23), May 30–June 02, 2023, Tubingen, Germany. ACM, New York, NY, USA, 8 pages, [doi], [PDF]
• Ke Li, Tim Rolff, Susanne Schmidt, Reinhard Bacher, Wim Leemans, and Frank Steinicke: Interacting with Neural Radiance Fields in Immersive Virtual Reality. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (CHI EA '23), April 23–28, 2023, Hamburg, Germany. ACM, New York, NY, USA. [doi]

2022

• Tim Rolff, H. Matthias Harms, Frank Steinicke, Simone Frintrop: GazeTransformer: Gaze Forecasting for Virtual Reality Using Transformer Networks, Pattern Recognition. DAGM GCPR 2022, Lecture Notes in Computer Science, vol 13485. Springer, [PDF]
• Tim Rolff, Niklas Stein, Markus Lappe, Frank Steinicke, Simone Frintrop: Metrics for Time-to-Event Prediction of Gaze Events, NeurIPS 2022 Gaze Meets ML Workshop, [PDF]
• Ke Li*, Tim Rolff*, Susanne Schmidt, Reinhard Bacher, Simone Frintrop, Wim Leemans, Frank Steinicke, Immersive Neural Graphics Primitives, [arXiv] , [code], 2022, *Equal contribution
• Tim Rolff, Frank Steinicke, Simone Frintrop: Gaze Mapping for Immersive Virtual Environments Based on Image Retrieval, Frontiers in Virtual Reality, 2022, [PDF]
• Tim Rolff, Frank Steinicke, and Simone Frintrop: When do Saccades begin? Prediction of Saccades as a Time-to-Event Problem, ACM Symposium on Eye Tracking Research & Applications, 2022, [PDF]

2020

• Tim Rolff, Marc Rautenhaus, Stephan Olbrich, Simone Frintrop: Segmenting Computer-Tomographic Scans of Ancient Clay Artefacts for Visual Analysis of Cuneiform Inscriptions, In: Vision, Modeling, and Visualization, 2020, ISBN: 978-3-03868-123-6, DOI:10.2312/vmv.20201185, [PDF]