Search Results for author: David Rauber

Found 3 papers, 2 papers with code

Semi-Supervised Segmentation based on Error-Correcting Supervision

no code implementations • ECCV 2020 • Robert Mendel, Luis Antonio de Souza Jr, David Rauber, João Paulo Papa, Christoph Palm

Apart from the supervised training on the labeled data, the segmentation network is judged by an additional network.

Segmentation

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OpenMIBOOD: Open Medical Imaging Benchmarks for Out-Of-Distribution Detection

1 code implementation • CVPR 2025 • Max Gutbrod, David Rauber, Danilo Weber Nunes, Christoph Palm

This paper introduces the Open Medical Imaging Benchmarks for Out-Of-Distribution Detection (OpenMIBOOD), a comprehensive framework for evaluating out-of-distribution (OOD) detection methods specifically in medical imaging contexts.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

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2018 Robotic Scene Segmentation Challenge

3 code implementations • 30 Jan 2020 • Max Allan, Satoshi Kondo, Sebastian Bodenstedt, Stefan Leger, Rahim Kadkhodamohammadi, Imanol Luengo, Felix Fuentes, Evangello Flouty, Ahmed Mohammed, Marius Pedersen, Avinash Kori, Varghese Alex, Ganapathy Krishnamurthi, David Rauber, Robert Mendel, Christoph Palm, Sophia Bano, Guinther Saibro, Chi-Sheng Shih, Hsun-An Chiang, Juntang Zhuang, Junlin Yang, Vladimir Iglovikov, Anton Dobrenkii, Madhu Reddiboina, Anubhav Reddy, Xingtong Liu, Cong Gao, Mathias Unberath, Myeonghyeon Kim, Chanho Kim, Chaewon Kim, Hye-Jin Kim, Gyeongmin Lee, Ihsan Ullah, Miguel Luna, Sang Hyun Park, Mahdi Azizian, Danail Stoyanov, Lena Maier-Hein, Stefanie Speidel

In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward kinematics and instrument CAD models.

Scene Segmentation Segmentation

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