11 to 20 of 88 Results
May 14, 2025 - SFB-TRR 161 B04 "Adaptive Algorithms for Motion Estimation"
Schmalfuss, Jenny; Oei, Victor; Mehl, Lukas; Bartsch, Madlen; Agnihotri, Shashank; Keuper, Margret; Bruhn, Andres, 2025, "RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo", https://doi.org/10.18419/DARUS-5047, DaRUS, V1
The RobustSpring dataset contains the image corruption data files for scene flow, optical flow and stereo estimation with the Spring dataset. Note that this repository contains only the Spring test data files. For easier handling, we organized them into sub-directories by image corruption type: brightness.zip : brightness image corruption contrast.... |
May 14, 2025 - SFB-TRR 161 INF "Collaboration Infrastructure"
Müller, Christoph; Ertl, Thomas, 2024, "Performance Data for the Visualisation of Time-Dependent Particles using DirectStorage", https://doi.org/10.18419/DARUS-4017, DaRUS, V2
Results of a series of performance measurements (frame times) to determine the impact of using the DirectStorage API for rendering time-dependent particle data sets in contrast to using traditional POSIX-style I/O APIs. |
Oct 25, 2024 - SFB-TRR 161 A08 "A Learning-Based Research Methodology for Visualization"
Angerbauer, Katrin; Van Wagoner, Phoenix; Halach, Tim; Vogelsang, Jonas; Hube, Natalie; Smith, Andria Lenae; Keplinger, Ksenia; Sedlmair, Michael, 2024, "Supplemental Material for the Paper: Is it Part of Me? Exploring Experiences of Inclusive Avatar Use For Visible and Invisible Disabilities in Social VR", https://doi.org/10.18419/DARUS-4426, DaRUS, V1
Supplemental Material for the paper titled: " Is it Part of Me? Exploring Experiences of Inclusive Avatar Use For Visible and Invisible Disabilities in Social VR" accepted for presentation at the ASSETS'24 conference. The structure of the folder is as following:
.
└── avatars
|── base avatars # base avatars generated with ReadyPlayer... |
Sep 16, 2024 - SFB-TRR 161 C06 "User-Adaptive Mixed Reality"
Chiossi, Francesco; Haliburton, Luke; Ou, Changkun; Butz, Andreas; Schmidt, Albrecht, 2024, "Dataset for "Short-Form Videos Degrade Our Capacity to Retain Intentions: Effect of Context Switching On Prospective Memory"", https://doi.org/10.18419/DARUS-3327, DaRUS, V1, UNF:6:7FzpUkbNmyXLFXVYJ8abKQ== [fileUNF]
Social media platforms use short, highly engaging videos to catch users’ attention. While the short-form video feeds popularized by TikTok are rapidly spreading to other platforms, we do not yet understand their impact on cognitive functions. We conducted a between-subjects experiment (𝑁 = 60) investigating the impact of engaging with TikTok, Twit... |
Sep 16, 2024 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Evers, Marina; Weiskopf, Daniel, 2024, "Supplementary Material for Uncertainty-aware Spectral Visualization", https://doi.org/10.18419/DARUS-4447, DaRUS, V1
In this supplemental material, we provide supplemental information (PDF document with derivations of the results presented in the paper and two additional use cases) and the supplementary video for uncertainty-aware spectral analysis. We model an uncertain time series as a multivariate Gaussian process. We propagate the uncertainty and explicitly c... |
Sep 2, 2024 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Reichmann, Luca; Hägele, David; Weiskopf, Daniel, 2024, "Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions", https://doi.org/10.18419/DARUS-4441, DaRUS, V1, UNF:6:WoQ4MNffz92VcvZ/qCGL5w== [fileUNF]
This dataset contains the supplemental material for "Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions". The contents and usage of this dataset are described in the README.md files. |
Aug 20, 2024 - SFB-TRR 161 INF "Collaboration Infrastructure"
Müller, Christoph, 2024, "SFB/Transregio 161 Data Management Plan 2023-2027", https://doi.org/10.18419/DARUS-4452, DaRUS, V1
The participating universities in SFB/Transregio 161 acknowledge the general importance of re-search data management as a vital issue for all of their work and provide increasing central sup-port for long-term accessibility and reusability of data, documentation of methods and tools and privacy protection. However, technical and organisational offe... |
Jul 30, 2024 - Visualisierungsinstitut der Universität Stuttgart
Gralka, Patrick; Müller, Christoph; Heinemann, Moritz; Reina, Guido; Weiskopf, Daniel; Ertl, Thomas, 2024, "Supplemental Material for "Power Overwhelming: The One With the Oscilloscopes"", https://doi.org/10.18419/DARUS-4256, DaRUS, V1, UNF:6:+e/WFL9E6WB+2FvGNOvcGA== [fileUNF]
Supplemental Material for "Power Overwhelming: The One With the Oscilloscopes". Contains the aggregated energy consumption data from the experiments in the paper. The application under test was MegaMol with two OpenGL-based sphere rasterization rendering methods (data static on GPU, data streaming to GPU) and OptiX-based sphere ray tracing. |
Jun 21, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
Bienroth, Denis; Charitakis, Natalie; Jaeger-Honz, Sabrina; Garkov, Dimitar; Elliott, David; Porrello, Enzo R.; Klein, Karsten; Nim, Hieu T.; Schreiber, Falk; Ramialison, Mirana, 2024, "Spatially Resolved Transcriptomics Mining in 3D and Virtual Reality Environments with VR-Omics (Software and Data)", https://doi.org/10.18419/DARUS-4254, DaRUS, V1
Here, we summarise available data and source code regarding the publication "Spatially Resolved Transcriptomics Mining in 3D and Virtual Reality Environments with VR-Omics". Abstract Spatially resolved transcriptomics (SRT) technologies produce complex, multi-dimensional data sets of gene expression information that can be obtained at subcellular s... |
Jun 19, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
Jaeger-Honz, Sabrina; Klein, Karsten; Schreiber, Falk, 2024, "Research Data Summary for: "Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data"", https://doi.org/10.18419/DARUS-4251, DaRUS, V1
Here, we summarise available data and source code regarding the publication "Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data". Abstract Computational methods such as molecular docking or molecular dynamics (MD) simulations have been developed to simulate and explore the interacti... |
