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Pattern Recognition

42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28 – October 1, 2020, Proceedings

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Zeynep Akata

    1. University of Tübingen, Tübingen, Germany

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  2. Andreas Geiger

    1. University of Tübingen, Tübingen, Germany

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  3. Torsten Sattler

    1. Czech Technical University in Prague, Prague, Czech Republic

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12544)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: DAGM GCPR 2020.

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About this book

This book constitutes the refereed proceedings of the 42nd German Conference on Pattern Recognition, DAGM GCPR 2020, which took place during September 28 until October 1, 2020. The conference was planned to take place in Tübingen, Germany, but had to change to an online format due to the COVID-19 pandemic.

The 34 papers presented in this volume were carefully reviewed and selected from a total of 89 submissions. They were organized in topical sections named: Normalizing Flow, Semantics, Physics, Camera Calibration and Computer Vision, Pattern Recognition, Machine Learning.

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Table of contents (34 papers)

  1. Front Matter

    Pages i-xv
    Download chapter PDF

  2. Characterizing the Role of a Single Coupling Layer in Affine Normalizing Flows

    • Felix Draxler, Jonathan Schwarz, Christoph Schnörr, Ullrich Köthe
    Pages 1-14

  3. Semantic Bottlenecks: Quantifying and Improving Inspectability of Deep Representations

    • Max Maria Losch, Mario Fritz, Bernt Schiele
    Pages 15-29

  4. Bias Detection and Prediction of Mapping Errors in Camera Calibration

    • Annika Hagemann, Moritz Knorr, Holger Janssen, Christoph Stiller
    Pages 30-43

  5. Learning to Identify Physical Parameters from Video Using Differentiable Physics

    • Rama Kandukuri, Jan Achterhold, Michael Moeller, Joerg Stueckler
    Pages 44-57

  6. Assignment Flow for Order-Constrained OCT Segmentation

    • Dmitrij Sitenko, Bastian Boll, Christoph Schnörr
    Pages 58-71

  7. Boosting Generalization in Bio-signal Classification by Learning the Phase-Amplitude Coupling

    • Abdelhak Lemkhenter, Paolo Favaro
    Pages 72-85

  8. Long-Tailed Recognition Using Class-Balanced Experts

    • Saurabh Sharma, Ning Yu, Mario Fritz, Bernt Schiele
    Pages 86-100

  9. Analyzing the Dependency of ConvNets on Spatial Information

    • Yue Fan, Yongqin Xian, Max Maria Losch, Bernt Schiele
    Pages 101-115

  10. Learning Monocular 3D Vehicle Detection Without 3D Bounding Box Labels

    • Lukas Koestler, Nan Yang, Rui Wang, Daniel Cremers
    Pages 116-129

  11. Observer Dependent Lossy Image Compression

    • Maurice Weber, Cedric Renggli, Helmut Grabner, Ce Zhang
    Pages 130-144

  12. Adversarial Synthesis of Human Pose from Text

    • Yifei Zhang, Rania Briq, Julian Tanke, Juergen Gall
    Pages 145-158

  13. Long-Term Anticipation of Activities with Cycle Consistency

    • Yazan Abu Farha, Qiuhong Ke, Bernt Schiele, Juergen Gall
    Pages 159-173

  14. Multi-stage Fusion for One-Click Segmentation

    • Soumajit Majumder, Ansh Khurana, Abhinav Rai, Angela Yao
    Pages 174-187

  15. Neural Architecture Performance Prediction Using Graph Neural Networks

    • Jovita Lukasik, David Friede, Heiner Stuckenschmidt, Margret Keuper
    Pages 188-201

  16. Discovering Latent Classes for Semi-supervised Semantic Segmentation

    • Olga Zatsarynna, Johann Sawatzky, Juergen Gall
    Pages 202-217

  17. Riemannian SOS-Polynomial Normalizing Flows

    • Jonathan Schwarz, Felix Draxler, Ullrich Köthe, Christoph Schnörr
    Pages 218-231

  18. Automated Water Segmentation and River Level Detection on Camera Images Using Transfer Learning

    • Rémy Vandaele, Sarah L. Dance, Varun Ojha
    Pages 232-245

  19. Does SGD Implicitly Optimize for Smoothness?

    • Václav Volhejn, Christoph Lampert
    Pages 246-259

  20. Looking Outside the Box: The Role of Context in Random Forest Based Semantic Segmentation of PolSAR Images

    • Ronny Hänsch
    Pages 260-274
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Editors and Affiliations

  • University of Tübingen, Tübingen, Germany

    Zeynep Akata, Andreas Geiger

  • Czech Technical University in Prague, Prague, Czech Republic

    Torsten Sattler

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