papers

Publications (6)

cs.CV2025

Mission Balance: Generating Under-represented Class Samples using Video Diffusion Models

Danush Kumar Venkatesh, Isabel Funke, Micha Pfeiffer +5

Computer-assisted interventions can improve intra-operative guidance, particularly through deep learning methods that harness the spatiotemporal information in surgical videos. How…

cs.CV2024

Exploring Semantic Consistency in Unpaired Image Translation to Generate Data for Surgical Applications

Danush Kumar Venkatesh, Dominik Rivoir, Micha Pfeiffer +4

In surgical computer vision applications, obtaining labeled training data is challenging due to data-privacy concerns and the need for expert annotation. Unpaired image-to-image tr…

cs.CV2022

Rethinking Anticipation Tasks: Uncertainty-aware Anticipation of Sparse Surgical Instrument Usage for Context-aware Assistance

Dominik Rivoir, Sebastian Bodenstedt, Isabel Funke +4

Intra-operative anticipation of instrument usage is a necessary component for context-aware assistance in surgery, e.g. for instrument preparation or semi-automation of robotic tas…

cs.CV2024

One model to use them all: Training a segmentation model with complementary datasets

Alexander C. Jenke, Sebastian Bodenstedt, Fiona R. Kolbinger +3

Understanding a surgical scene is crucial for computer-assisted surgery systems to provide any intelligent assistance functionality. One way of achieving this scene understanding i…

cs.CV2020

Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration

Dominik Rivoir, Sebastian Bodenstedt, Felix von Bechtolsheim +3

Estimating the remaining surgery duration (RSD) during surgical procedures can be useful for OR planning and anesthesia dose estimation. With the recent success of deep learning-ba…

cs.CV2026

A benchmark for video-based laparoscopic skill analysis and assessment

Isabel Funke, Sebastian Bodenstedt, Felix von Bechtolsheim +7

Laparoscopic surgery is a complex surgical technique that requires extensive training. Recent advances in deep learning have shown promise in supporting this training by enabling a…