E-raamat: Pattern Recognition: 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 - October 1, 2021, Proceedings

Machine Learning and Optimization.- Sublabel-Accurate Multilabeling
Meets Product Label Spaces.- InfoSeg: Unsupervised Semantic Image
Segmentation with Mutual Information Maximization.- Sampling-free Variational
Inference for Neural Networks with Multiplicative Activation Noise.-
Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from
Biased Data.- Revisiting Consistency Regularization for Semi-Supervised
Learning.- Learning Robust Models Using the Principle of Independent Causal
Mechanisms.- Reintroducing Straight-Through Estimators as Principled Methods
for Stochastic Binary Networks.- Bias-Variance Tradeoffs in Single-Sample
Binary Gradient Estimators.- End-to-end Learning of Fisher Vector Encodings
for Part Features in Fine-grained Recognition.- Investigating the Consistency
of Uncertainty Sampling in Deep Active Learning.- ScaleNet: An Unsupervised
Representation Learning Method for Limited Information.- Actions, Events, and
Segmentation.- A New Split for Evaluating True Zero-Shot Action Recognition.-
Video Instance Segmentation with Recurrent Graph Neural Networks.-
Distractor-Aware Video Object Segmentation.- (SP)^2Net for Generalized
Zero-Label Semantic Segmentation.- Contrastive Representation Learning for
Hand Shape Estimation.- Fusion-GCN: Multimodal Action Recognition using Graph
Convolutional Networks.- FIFA: Fast Inference Approximation for Action
Segmentation.- Hybrid SNN-ANN: Energy-Efficient Classification and Object
Detection for Event-Based Vision.- A Comparative Study of PnP and Learning
Approaches to Super-Resolution in a Real-World Setting.- Merging-ISP:
Multi-Exposure High Dynamic Range Image Signal Processing.- Spatiotemporal
Outdoor Lighting Aggregation on Image Sequences.- Generative Models and
Multimodal Data.- AttrLostGAN: Attribute Controlled Image Synthesis from
Reconfigurable Layout and Style.- Learning Conditional Invariance through
Cycle Consistency.- CAGAN: Text-To-Image Generation with Combined Attention
Generative Adversarial Networks.- TxT: Crossmodal End-to-End Learning with
Transformers.- Diverse Image Captioning with Grounded Style.- Labeling and
Self-Supervised Learning.- Leveraging Group Annotations in Object Detection
Using Graph-Based Pseudo-Labeling.- Quantifying Uncertainty of Image
Labelings Using Assignment Flows.- Implicit and Explicit Attention for
Zero-Shot Learning.- Self-Supervised Learning for Object Detection in
Autonomous Driving.- Assignment Flows and Nonlocal PDEs on Graphs.-
Applications.- Viewpoint-Tolerant Semantic Segmentation for Aerial
Logistics.- T6D-Direct: Transformers for Multi-Object 6D Pose Direct
Regression.- TetraPackNet: Four-Corner-Based Object Detection in Logistics
Use-Cases.- Detecting Slag Formations with Deep Convolutional Neural
Networks.- Virtual Temporal Samples for Recurrent Neural Networks: applied to
semantic segmentation in agriculture.- Weakly Supervised Segmentation
Pre-training for Plant Cover Prediction.- How Reliable Are
Out-of-Distribution Generalization Methods for Medical Image Segmentation?.-
3D Modeling and Reconstruction.- Clustering Persistent Scatterer Points Based
on a Hybrid Distance Metric.- CATEGORISE: An Automated Framework for
Utilizing the Workforce of the Crowd for Semantic Segmentation of 3D Point
Clouds.- Zero-Shot remote sensing image super resolution based on image
continuity and self-tessellations.- A Comparative Survey of Geometric Light
Source Calibration Methods.- Quantifying point cloud realism through
adversarially learned latent representations.- Full-Glow: Fully conditional
Glow for more realistic image generation.- Multidirectional Conjugate
Gradients for Scalable Bundle Adjustment.