Search Results for author: Thomas Kurmann

Found 6 papers, 3 papers with code

Learning How To Robustly Estimate Camera Pose in Endoscopic Videos

1 code implementation17 Apr 2023 Michel Hayoz, Christopher Hahne, Mathias Gallardo, Daniel Candinas, Thomas Kurmann, Maximilian Allan, Raphael Sznitman

Purpose: Surgical scene understanding plays a critical role in the technology stack of tomorrow's intervention-assisting systems in endoscopic surgeries.

3D Reconstruction Optical Flow Estimation +3

Fused Detection of Retinal Biomarkers in OCT Volumes

no code implementations16 Jul 2019 Thomas Kurmann, Pablo Márquez-Neila, Siqing Yu, Marion Munk, Sebastian Wolf, Raphael Sznitman

In this context, we present a method that automatically predicts the presence of biomarkers in OCT cross-sections by incorporating information from the entire volume.

Deep Multi Label Classification in Affine Subspaces

no code implementations10 Jul 2019 Thomas Kurmann, Pablo Marquez Neila, Sebastian Wolf, Raphael Sznitman

We evaluate the method using two MLC medical imaging datasets and show a large performance increase compared to previous multi-label frameworks.

Classification General Classification +3

2017 Robotic Instrument Segmentation Challenge

3 code implementations18 Feb 2019 Max Allan, Alex Shvets, Thomas Kurmann, Zichen Zhang, Rahul Duggal, Yun-Hsuan Su, Nicola Rieke, Iro Laina, Niveditha Kalavakonda, Sebastian Bodenstedt, Luis Herrera, Wenqi Li, Vladimir Iglovikov, Huoling Luo, Jian Yang, Danail Stoyanov, Lena Maier-Hein, Stefanie Speidel, Mahdi Azizian

In mainstream computer vision and machine learning, public datasets such as ImageNet, COCO and KITTI have helped drive enormous improvements by enabling researchers to understand the strengths and limitations of different algorithms via performance comparison.

Benchmarking Person Re-Identification +2

Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery

1 code implementation18 Oct 2017 Thomas Kurmann, Pablo Marquez Neila, Xiaofei Du, Pascal Fua, Danail Stoyanov, Sebastian Wolf, Raphael Sznitman

An additional advantage of our approach is that instrument detection at test time is achieved while avoiding the need for scale-dependent sliding window evaluation.

Pose Estimation Test

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