Florian Philipp Stilz

PhD Student @ CAMP Lab, Technical University of Munich & PhD Student @ CAMMA Lab, University of Strasbourg

Currently, I am pursuing a PhD in computer science with focus on multi-modality foundation models for intraoperative surgical procedures at the Technical University of Munich and University of Strasbourg, which is co-supervised by Prof. Nassir Navab and Prof. Nicolas Padoy. My main research interests are utilizing modern Deep Learning methods for the areas of 3D Computer Vision. E.g. Neural Rendering and 3D/4D Reconstruction as well as Multi-modal Deep Learning for both Natural Language Processing and Computer Vision.

florian.stilz@tum.de

Publications

CliPPER: Contextual Video-Language Pretraining on Long-form Intraoperative Surgical Procedures for Event Retrieval

Florian Philipp Stilz, Vinkle Srivastav, Nassir Navab, Nicolas Padoy

Under peer review

FLex: Joint Pose and Dynamic Radiance Fields Optimization for Stereo Endoscopic Videos

Florian Philipp Stilz, Mert Asim Karaoglu, Felix Tristram, Nassir Navab, Benjamin Busam, Alexander Ladikos

International Journal of Computer Assisted Radiology and Surgery, 2025

More Research

Learning World Models by Self-supervised Exploration

Technical University of Munich

Oct 2022 - Feb 2023 Munich, Germany

Supervisor: Lennart Röstel

We worked on an adapted version of Plan2Explore, where an agent builds a world model trained in a self-supervised manner. The model was tested on the Stacker task in the DeepMind Control Suite

Project

Transposition Equivariant Music Key Signature Estimation

Technical University of Munich

May 2022 - Jan 2023 Munich, Germany

Supervisor: Dr. Vladimir Golkov

I developed a global key signature estimation model for audio files. It additionally predicts the tonic as well as the genre of a music piece. The final architecture is called PitchClassNet and is music transposition equivariant by design. The model achieves competitive results with only a fraction of parameters compared to other state-of-the-art methods.

Project

Scientific Paper Classification using Visual and Textual Features

Technical University of Munich

April 2022 - Oct 2022 Munich, Germany

Supervisor: Prof. Matthias Nießner

In this project I worked on analyzing scientific publications by performing several classification tasks like Citation/Year, Year, and Category. The tasks are achieved by utilizing both visual and textual features. The visual features are the front page and figures from a given publication paper. The textual features are the title and the abstract of a given publication. In addition an entirely new dataset was generated with more than 200k publications.

Project

3D Visual Grounding with Transformers

Technical University of Munich

April 2022 - July 2022 Munich, Germany

Supervisor: Dave Zhenyu Chen

This work focuses on developing a transformer architecture for bounding box prediction around a target object that is described by a natural language description, beating the starting baseline by more than 2% IoU accuracy.

Project

Segmentation of Medical Records with Natural Language Processing Tools

Technical University of Denmark

Jan 2021 - May 2021 Lyngby, Denmark

Supervisor: Prof. Ole Winther

My B.Sc. thesis on segmenting medical abstracts via Named Entity Recognition. The main focus was put on using different BERT architectures to classify important medical classes like e.g. "Diagnosis", "Symptoms", and so on within medical abstracts for rare diseases

Project