2 citations · 2 across the 7 of their papers we have counts for
6 papers · 1 filter
HeiCo-FOCUS: A Clinically Grounded Dataset for Long-Context Video Understanding
Leon Mayer, Lucas Luttner, Patrick Godau +42
Recent advances in Vision-Language Models (VLMs) have led to rapid progress in video understanding across a wide range of benchmark tasks. However, existing evaluations largely foc…
Towards Application Aligned Synthetic Surgical Image Synthesis
Danush Kumar Venkatesh, Stefanie Speidel
The scarcity of annotated surgical data poses a significant challenge for developing deep learning systems in computer-assisted interventions. While diffusion models can synthesize…
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…
Data Augmentation for Surgical Scene Segmentation with Anatomy-Aware Diffusion Models
Danush Kumar Venkatesh, Dominik Rivoir, Micha Pfeiffer +2
In computer-assisted surgery, automatically recognizing anatomical organs is crucial for understanding the surgical scene and providing intraoperative assistance. While machine lea…
SurgicaL-CD: Generating Surgical Images via Unpaired Image Translation with Latent Consistency Diffusion Models
Danush Kumar Venkatesh, Dominik Rivoir, Micha Pfeiffer +1
Computer-assisted surgery (CAS) systems are designed to assist surgeons during procedures, thereby reducing complications and enhancing patient care. Training machine learning mode…
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…