Full Description
This book constitutes the proceedings of the 45th Annual Conference of the German Association for Pattern Recognition, DAGM-GCPR 2023, which took place in Heidelberg, Germany, during September 19-22, 2023. The 40 full papers included in these proceedings were carefully reviewed and selected from 76 submissions. They were organized in topical sections as follows: Segmentation and action recognition; 3D reconstruction and neural rendering; Photogrammetry and remote sensing; Pattern recognition in the life sciences; Interpretable machine learning; Weak supervision and online learning; Robust models.
Contents
Segmentation and action recognition.- Score-Based Generative Models for Medical Image Segmentation using Signed Distance Functions.- A Trimodal Dataset: RGB, Thermal, and Depth for Human Segmentation and Temporal Action Detection.- Airborne-Shadow: Towards Fine-Grained Shadow Detection in Aerial Imagery.- UGainS: Uncertainty Guided Anomaly Instance Segmentation.- Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition.- 3D reconstruction and neural rendering.- LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds.- A Network Analysis for Correspondence Learning via Linearly-Embedded Functions.- HiFiHR: Enhancing 3D Hand Reconstruction from a Single Image via High-Fidelity Texture.- Point2Vec for Self-Supervised Representation Learning on Point Clouds.- FullFormer: Generating Shapes Inside Shapes.- GenLayNeRF: Generalizable Layered Representations with 3D ModelAlignment for Human View Synthesis.- RC-BEVFusion: A Plug-In Module for Radar-Camera Bird's Eye View Feature Fusion.- Parallax-aware Image Stitching based on Homographic Decomposition.- Photogrammetry and remote sensing.- DustNet: Attention to Dust.- Leveraging Bioclimatic Context for Supervised and Self-Supervised Land Cover Classification.- Automatic Reverse Engineering: Creating computer-aided design (CAD) models from multi-view images.- Characterization of out-of-distribution samples from uncertainty maps using supervised machine learning.- Underwater multiview stereo using axial camera models.- Pattern recognition in the life sciences.- 3D Retinal Vessel Segmentation in OCTA Volumes: Annotated Dataset MORE3D and Hybrid U-Net with Flattening Transformation.- M(otion)-mode Based Prediction of Ejection Fraction using Echocardiograms.- Improving Data Efficiency for Plant Cover Prediction with Label Interpolation and Monte-Carlo Cropping.- Learning Channel Importance for High Content Imaging with Interpretable Deep Input Channel Mixing.- Self-Supervised Learning in Histopathology: New Perspectives for Prostate Cancer Grading.- Interpretable machine learning.- DeViL: Decoding Vision features into Language.- Zero-shot Translation of Attention Patterns in VQA Models to Natural Language.- Beyond Debiasing: Actively Steering Feature Selection via Loss Regularization.- Simplified Concrete Dropout - Improving the Generation of Attribution Masks for Fine-grained Classification.- Weak supervision and online learning.- Best Practices in Active Learning for Semantic Segmentation.- COOLer: Class-Incremental Learning for Appearance-Based Multiple Object Tracking.- Label Smarter, Not Harder: CleverLabel for Faster Annotation of Ambiguous Image Classification with Higher Quality.- Speeding Up Online Self-Supervised Learning by Exploiting Its Limitations.- Text-to-feature diffusion for audio-visual few-shot learning.- Correlation Clustering of Bird Sounds.- MargCTGAN: A ``Marginally'' Better CTGAN for the Low Sample Regime.- Robust models.- Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks Adversarial Perturbations Straight on JPEG Coefficients.- Certified Robust Models with Slack Control and Large Lipschitz Constants.- Multiclass Alignment of Confidence and Certainty for Network Calibration.- Drawing the Same Bounding Box Twice? Coping Noisy Annotations in Object Detection with Repeated Labels.- An Evaluation of Zero-Cost Proxies - from Neural Architecture Performance Prediction to Model Robustness.
