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ORCID46th GCPR 2024: Konstanz, Germany - Part I
- Daniel Cremers
, Zorah Lähner, Michael Moeller, Matthias Nießner, Björn Ommer, Rudolph Triebel:
Pattern Recognition - 46th DAGM German Conference, DAGM GCPR 2024, Munich, Germany, September 10-13, 2024, Proceedings, Part I. Lecture Notes in Computer Science 15297, Springer 2025, ISBN 978-3-031-85180-3
Clustering and Segmentation
- Philip Matthias Winter, Maria Wimmer, Astrid Berg, David Major, Dimitrios Lenis, Theresa Neubauer, Gaia Romana De Paolis, Johannes Novotny, Sophia Ulonska, Katja Bühler:
PARMESAN: Parameter-Free Memory Search and Transduction for Dense Prediction Tasks. 3-20 - Jannik Irmai, Bjoern Andres:
A State-of-the-Art Cutting Plane Algorithm for Clique Partitioning. 21-36 - Apostolos Panagiotopoulos, Mandy Toh, Triantafyllos Afouras, Yuki M. Asano:
Self-supervised Semantic Segmentation from Audio-Visual Data. 37-52 - Johannes Künzel, Anna Hilsmann, Peter Eisert:
BTSeg: Barlow Twins Regularization for Domain Adaptation in Semantic Segmentation. 53-67
Learning Techniques
- Tobias Lorenz, Marta Kwiatkowska, Mario Fritz:
FullCert: Deterministic End-to-End Certification for Training and Inference of Neural Networks. 71-85 - Alfonso Taboada Warmerdam, Mathilde Caron, Yuki M. Asano:
Self-masking Networks for Unsupervised Adaptation. 86-102 - Zhehao Liang, Yanqing Luo, Marvin Beese, Patrik Reiske:
A Theoretical Formulation on the Use of Multiple Positive Views in Contrastive Learning. 103-116 - Dominik Werner Wolf, Prasannavenkatesh Balaji, Alexander Braun, Markus Ulrich:
Decoupling of Neural Network Calibration Measures. 117-130 - Cathrin Elich, Lukas Kirchdorfer, Jan Mathias Köhler, Lukas Schott:
Examining Common Paradigms in Multi-task Learning. 131-147 - Tobias Lingenberg, Markus Reuter, Gopika Sudhakaran, Dominik Gojny, Stefan Roth, Simone Schaub-Meyer:
DIAGen: Semantically Diverse Image Augmentation with Generative Models for Few-Shot Learning. 148-163 - Morris Florek, David Tschirschwitz, Björn Barz, Volker Rodehorst:
Efficient and Discriminative Image Feature Extraction for Universal Image Retrieval. 164-180 - Arian Mousakhan, Thomas Brox, Jawad Tayyub:
Anomaly Detection with Conditioned Denoising Diffusion Models. 181-195
Medical and Biological Applications
- Ahmed Tawfik Aboukhadra, Nadia Robertini, Jameel Malik, Ahmed Elhayek, Gerd Reis, Didier Stricker:
SurgeoNet: Realtime 3D Pose Estimation of Articulated Surgical Instruments from Stereo Images Using a Synthetically-Trained Network. 199-211 - Olivier Morelle, Thomas Schultz:
Foundation Models Permit Retinal Layer Segmentation Across OCT Devices. 212-223 - Jannik Presberger, Rashmiparvathi Keshara, David Stein, Yung Hae Kim, Anne Grapin-Botton, Bjoern Andres:
Correlation Clustering of Organoid Images. 224-240 - Lukás Picek, Lukás Neumann, Jirí Matas:
Animal Identification with Independent Foreground and Background Modeling. 241-257 - Mayar Lotfy, Anna Alperovich, Tommaso Giannantonio, Björn Barz, Xiaohan Zhang, Felix Holm, Nassir Navab, Felix Boehm, Carolin Schwamborn, Thomas K. Hoffmann, Patrick J. Schuler:
Robust Tumor Segmentation with Hyperspectral Imaging and Graph Neural Networks. 258-274 - Lukas Glaszner, Martin Zach:
Bigger Isn't Always Better: Towards a General Prior for Medical Image Reconstruction. 275-291
Uncertainty and Explainability
- Simon Schrodi, Karim Farid, Max Argus, Thomas Brox:
Latent Diffusion Counterfactual Explanations. 295-311 - Lu Sang, Abhishek Saroha, Maolin Gao, Daniel Cremers:
Enhancing Surface Neural Implicits with Curvature-Guided Sampling and Uncertainty-Augmented Representations. 312-328 - Yuchang Jiang, Vivien Sainte Fare Garnot, Konrad Schindler, Jan Dirk Wegner:
Uncertainty Voting Ensemble for Imbalanced Deep Regression. 329-343 - Lukas Kirchdorfer, Cathrin Elich, Simon Kutsche, Heiner Stuckenschmidt, Lukas Schott, Jan Mathias Köhler:
Analytical Uncertainty-Based Loss Weighting in Multi-task Learning. 344-361
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