My research involves computer graphics, real-time rendering, numerical simulation, and Deep Learning. Currently, I’m working on a differentiable PISO fluid solver in PyTorch. Previously, I’ve worked on 3D smoke reconstruction from video using differentiable rendering.
Since October 2019 I’m a Ph.D. candidate in Nils Thuerey’s group after recieving my M.Sc. and B.Sc. degrees in Informatics: Games Engineering at TUM.
Contact
E-mail: franzer (at) in.tum.de
Room: 02.13.055
Publications
- A. Franz, B. Solenthaler and N. Thuerey, “Learning to Estimate Single-View Volumetric Flow Motions without 3D Supervision”, ICLR 2023 ☛ [Project]
- M. Chu et al., “Physics informed neural fields for smoke reconstruction with sparse data”, SIGGRAPH 2022 ☛ [Paper]
- A. Franz, B. Solenthaler and N. Thuerey, “Global Transport for Fluid Reconstruction with Learned Self-Supervision”, CVPR 2021 ☛ [Project]
- Y. Xie* , A. Franz* and M. Chu* and N. Thuerey, “tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow”, SIGGRAPH 2018, (*Similar contributions) ☛ [Project]
Theses
- Aleksandra Franz, “Deep-Learning based Super-Resolution for Games”, M.Sc. Thesis, Technische Universität München, August 2019. (English)
- Aleksandra Franz, “Synthesizing Smoke Datasets with Generative Adversarial Networks”, B.Sc. Thesis, Technische Universität München, August 2017. (English)
Teaching
- Computer Games Laboratory (Summer 2022, Winter 2022/32, 2023/24, and 2024/25)
- Grundlagen: Algorithmen und Datenstrukturen (Summer 2021 and 2023)
- Seminar Deep Learning in Computer Graphics (Summer 2020)