Pattern Recognition, 1st ed. 2021 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28 – October 1, 2020, Proceedings Image Processing, Computer Vision, Pattern Recognition, and Graphics Series

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.

Normalizing Flow, Semantics, Physics, Camera Calibration.- Characterizing The Role of A Single Coupling Layer in Affine Normalizing Flows.- Semantic Bottlenecks: Quantifying & Improving Inspectability of Deep Representations.- Bias Detection and Prediction of Mapping Errors in Camera Calibration.- Learning to Identify Physical Parameters from Video Using Differentiable Physics.- Computer Vision, Pattern Recognition, Machine Learning.- Assignment Flow For Order-Constrained OCT Segmentation.- Boosting Generalization in Bio-Signal Classification by Learning the Phase-Amplitude Coupling.- Long-Tailed Recognition Using Class-Balanced Experts.- Analyzing the Dependency of ConvNets on Spatial Information.- Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels.- Observer Dependent Lossy Image Compression.- Adversarial Synthesis of Human Pose from Text.- Long-Term Anticipation of Activities with Cycle Consistency.- Multi-Stage Fusion for One-click Segmentation.- Neural Architecture Performance Prediction Using Graph Neural Networks.- Discovering Latent Classes for Semi-Supervised Semantic Segmentation.- Riemannian SOS-Polynomial Normalizing Flows.- Automated water segmentation and river level detection on camera images using transfer learning.- Does SGD Implicitly Optimize for Smoothness.- Looking outside the box: The role of context in Random Forest based semantic segmentation of PolSAR images.- Haar Wavelet based Block Autoregressive Flows for Trajectories.- Center3D: Center-based Monocular 3D Object Detection with Joint Depth Understanding.- Constellation Codebooks for Reliable Vehicle Localization.- Towards Bounding-Box Free Panoptic Segmentation.- Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks.- Unsupervised Part Discovery by Unsupervised Disentanglement.- On the Lifted Multicut Polytope for Trees.- Conditional Invertible Neural Networks for Diverse Image-to-Image Translation.- Image Inpainting with Learnable Feature Imputation.- 4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving.- Inline Double Layer Depth Estimation with Transparent Materials.- A Differentiable Convolutional Distance Transform Layer for Improved Image Segmentation.- PET-guided Attention Network for Segmentation of Lung Tumors from PET/CT images.- Self-supervised Disentanglement of Modality-specific and Shared Factors Improves Multimodal Generative Models.- Multimodal semantic forecasting based on conditional generation of future features.