2 citations · 4 across the 20 of their papers we have counts for
10 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…
Looking Beyond the Scale: Do Surgical Skill Models Learn Transferable Representations Across Assessment Rubrics?
Hanna Hoffmann, Felix von Bechtolsheim, Stefanie Speidel +1
Vision-based surgical skill assessment has shown strong in-domain results, yet a fundamental question remains unasked: do these models learn transferable representations of surgica…
Understanding Multimodality in Generative Behavioral Cloning
Lorenzo Mazza, Massimiliano Datres, Ariel Rodriguez +3
Behavioral cloning becomes challenging when the same observation admits several valid actions. We study how generative behavioral-cloning policies represent such multimodal expert…
OSS: Open Suturing Skills Vision-Based Assessment Challenge 2024-2025
Hanna Hoffmann, Setareh Bady, Claas de Boer +54
Achieving high levels of surgical skill through effective training is essential for optimal patient outcomes. Automated, data-driven skill assessment holds significant potential to…
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
An Open-Source Robotics Research Platform for Autonomous Laparoscopic Surgery
Ariel Rodriguez, Lorenzo Mazza, Martin Lelis +4
Autonomous robot-assisted surgery demands reliable, high-precision platforms that strictly adhere to the safety and kinematic constraints of minimally invasive procedures. Existing…
LAR-MoE: Latent-Aligned Routing for Mixture of Experts in Robotic Imitation Learning
Ariel Rodriguez, Chenpan Li, Lorenzo Mazza +5
Imitation learning enables robots to acquire manipulation skills from demonstrations, yet deploying a policy across tasks with heterogeneous dynamics remains challenging, as models…
The Dresden Dataset for 4D Reconstruction of Non-Rigid Abdominal Surgical Scenes
Reuben Docea, Rayan Younis, Yonghao Long +10
The D4D Dataset provides paired endoscopic video and high-quality structured-light geometry for evaluating 3D reconstruction of deforming abdominal soft tissue in realistic surgica…
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…
Supervised Mixture-of-Experts for Surgical Grasping and Retraction
Lorenzo Mazza, Ariel Rodriguez, Rayan Younis +6
Imitation learning has achieved remarkable success in robotic manipulation, yet its application to surgical robotics remains challenging due to data scarcity, constrained workspace…