Document Analysis and Recognition – ICDAR 2021

<p>Historical Document Analysis 1.- BoundaryNet: An Attentive Deep Network with Fast Marching Distance Maps for Semi-automatic Layout Annotation.- Pho(SC)Net: An Approach Towards Zero-shot Word Image Recognition in Historical Documents.- Versailles-FP dataset: Wall Detection in Ancient Floor Plans.- Graph Convolutional Neural Networks for Learning Attribute Representations for Word Spotting.- Context Aware Generation of Cuneiform Signs.- Adaptive Scaling for Archival Table Structure Recognition.- Document Analysis Systems.- LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment.- VSR: A Unified Framework for Document Layout Analysis combining Vision, Semantics and Relations.- Layout-Parser:&nbsp; A Unified Toolkit for Deep Learning Based Document Image Analysis.- Understanding and Mitigating the Impact of Model Compression for Document Image Classification.- Hierarchical and Multimodal Classification of Images from Soil Remediation Reports.- Competition and Collaboration in Document Analysis and Recognition.- Handwriting Recognition.- 2D Self-Attention Convolutional Recurrent Network for Offline Handwritten Text Recognition.- Handwritten Text Recognition with Convolutional Prototype Network and Most Aligned Frame Based CTC Training.- Online Spatio-Temporal 3D Convolutional Neural Network for Early Recognition of Handwritten Gestures.- Mix-Up Augmentation for Oracle Character Recognition with Imbalanced Data Distribution.- Radical Composition Network for Chinese Character Generation.- SmartPatch: Improving Handwritten Word Imitation with Patch Discriminators.- Scene Text Detection and Recognition.- Reciprocal Feature Learning via Explicit and Implicit Tasks in Scene Text Recognition.- Text Detection by Jointly Learning Character and Word Regions.- Vision Transformer for Fast and Efficient Scene Text Recognition.- Look, Read and Ask: Learning to Ask Questions by Reading Text in Images.- CATNet: Scene Text Recognition Guided by Concatenating Augmented Text Features.- Explore Hierarchical Relations Reasoning and Global Information Aggregation.- Historical Document Analysis 2.- One-Model Ensemble-Learning for Text Recognition of Historical Printings.- On the use of attention in deep learning based denoising method for ancient Cham inscription images.- Visual FUDGE: Form Understanding via Dynamic Graph Editing.- Annotation-Free Character Detection in Historical Vietnamese Stele Images.- Document Image Processing.- DocReader: Bounding-Box Free Training of a Document Information Extraction Model.- Document Dewarping with Control Points.- Unknown-box Approximation to Improve Optical Character Recognition Performance.- Document Domain Randomization for Deep Learning Document Layout Extraction.- NLP for Document Understanding.- Distilling the Documents for Relation Extraction by Topic Segmentation.- LAMBERT: Layout-Aware Language Modeling for Information Extraction.- ViBERTgrid: A Jointly Trained Multi-Modal 2D Document Representation for Key Information Extraction from Documents.- Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts.- Graphics, Diagram, and Math Recognition.- Towards an efficient framework for Data Extraction from Chart Images.- Geometric Object 3D Reconstruction From Single Line Drawings Image Based on a Network for Classification and Sketch Extraction.- DiagramNet: Hand-drawn Diagram Recognition using Visual Arrow-relation Detection.- Formula Citation Graph Based Mathematical Information Retrieval.</p>