The Transregional Collaborative Research Centre 161 “Quantitative Methods for Visual Computing” is an interdisciplinary research centre at the University of Stuttgart and the University of Konstanz, funded by Deutsche Forschungsgemeinschaft (DFG) under project number 251654672. Ulm University and Ludwig-Maximilians-Universität München are participating institutions in the second and third funding period. The Max Planck Institute for Biological Cybernetics in Tübingen in was a participating institution in the first funding period.

The goal of SFB/Transregio 161 is establishing the paradigm of quantitative science in the field of visual computing, which is a long-term endeavour requiring a fundamental research effort broadly covering four research areas, namely quantitative models and measures, adaptive algorithms, interaction and applications. In the third funding period, which started in 2023, new research directions are being approached. One is visual explainability, assessing and quantifying how well the users of a visualisation system understand the phenomena shown visually. The second direction targets mixed reality, covering all forms of augmented and virtual reality as a cross-cutting field of various visual computing subfields, irrespective of applied technology. The third research theme aims to bring research results in the world, moving away from experiments in the laboratory and in the wild to openly accessible applications that provide research results, methods, data sets, and other outcomes from SFB/Transregio 161 to a wide range of stakeholders in academia, industry, teaching, and society in general.

In SFB/Transregio 161, approximately 40 scientists in the fields of computer science, visualisation, computer vision, human computer interaction, linguistics and applied psychology are jointly working on improving the quality of future visual computing methods and applications.

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

3,321 to 3,330 of 3,681 Results
Cascading Style Sheet - 14.6 KB - MD5: 9f54e6414f87e0d14b9e966f19a174f9
Javascript Code - 4.3 KB - MD5: 8161741c7647ed16d2d97fd6963c1a33
Javascript Code - 12.1 KB - MD5: d250dcb52a9a7649c7c789728917821f
Cascading Style Sheet - 765.1 KB - MD5: e1a4c5904e6d6e8ef1859b6d4b6631a3
Javascript Code - 739.4 KB - MD5: 08736e10f48c78add464c26d15a3efce
Cascading Style Sheet - 548.2 KB - MD5: c31afaf0f6975bb47f2bfb878f1dac1d
Javascript Code - 271.0 KB - MD5: 04f1c5fe87f35872f79e3578f3462bcc
Python Source Code - 3.9 KB - MD5: d698f9410ca376102cc2b413d5be4d9d
Cascading Style Sheet - 3.7 KB - MD5: d7269c016b9132b559c17672714db06c
Add Data

Log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.