DEXHELPP develops new methods to support analysis, planning and control in health care by combining decision analysis, data security, data management, statistics, mathematical modelling, simulation and visual analysis.
Together with Rhomberg Bau GmbH and convex ZT GmbH, VRVis is developing a concept for the use of Boston Dynamic's robot dog "Spot" for autonomous, immersive construction site documentation.
WIBSTAC addresses the usage of wide baseline stereo 3D reconstruction for medium- and long-range mapping of the Martian surface, based on imagery from panoramic rover camera instruments.
The INDIGO research team is systematically documenting the graffiti on Vienna's Donaukanal, using these photos to create a digital twin of the walls. VRVis is currently contributing its technological expertise to the project.
Businesses go smart with Data Science: with the help of visual data analysis, machine learning, deep learning, data mining and visual data processing we help companies to fully exploit the potential of their data.
No blind spots on train roofs thanks to depth cameras.
The applied research project Lightbox 2.0 focuses on the development of a photogrammetric 3D scanner for automatic and deep learning-based modeling of all kinds of keys.
Support for planetary research: Visual analysis of reconstructions of the Mars surface and view planning for rover camera instruments.
The "Mars-DL" project is investigating how a deep learning system can support the research work of planetary scientists through object and pattern recognition. For this project VRVis has extended the functionality of PRo3D to automatically render shatter cone training images.
Virtual exploration and geological analysis of reconstructed Mars surfaces and rock outcrops.
Visual computing for medicine: image processing solutions for new applications in radiology.
ARCHES - Accessible Resources for Cultural Heritage EcoSystems was an EU-funded Horizon2020 project coordinated by VRVis.