My research focuses on 3D vision. I am interested in how machines can infer 3D representations from sparse observations. Further, I am big enthusiast of neural scene representations. I currently investigate how scenes are best represented for machines using deep neural networks.
I studied BSc Mathematics at the University of Cologne, Germany. During my Bachelor studies, I spent one year at the University of Barcelona, Spain, funded by the ERASMUS program. Following my interest in computer science, I then moved to Scotland to gain my Master’s degree in Advanced Computer Science at the University of St Andrews. In October 2018, I started my PhD in computer vision / machine learning in the AVG group at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, under the supervision of Andreas Geiger.
Feel free to reach out to me via e-mail for any inquiries!
|Oct 10, 2021||Our CAMPARI paper got accepted to 3DV’21|
|Sep 29, 2021||Our Shapes as Points points paper got accepted to NeurIPS’21 (oral)|
|Jul 12, 2021||I was invited to give a talk at the AIT lab (ETH) about generative neural scene representations.|
|Jun 21, 2021||We recieved the CVPR’21 best paper award for our GIRAFFE project|
|May 12, 2021||I was invited to give a talk about Generative Neural Scene Representations at Amazon Research.|
- Occupancy Networks: Learning 3D Reconstruction in Function SpaceIn Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2019
- Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D SupervisionIn Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2020
- GIRAFFE: Representing Scenes as Compositional Generative Neural Feature FieldsIn Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2021