Document Layout Analysis
36 papers with code • 4 benchmarks • 9 datasets
"Document Layout Analysis is performed to determine physical structure of a document, that is, to determine document components. These document components can consist of single connected components-regions [...] of pixels that are adjacent to form single regions [...] , or group of text lines. A text line is a group of characters, symbols, and words that are adjacent, “relatively close” to each other and through which a straight line can be drawn (usually with horizontal or vertical orientation)." L. O'Gorman, "The document spectrum for page layout analysis," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 11, pp. 1162-1173, Nov. 1993.
Image credit: PubLayNet: largest dataset ever for document layout analysis
Benchmarks
These leaderboards are used to track progress in Document Layout Analysis
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Libraries
Use these libraries to find Document Layout Analysis models and implementations
PubLayNet
RVL-CDIP
HJDataset
ICDAR 2021
UrduDoc
Latest papers with no code
Performance Enhancement Leveraging Mask-RCNN on Bengali Document Layout Analysis
We trained a special model called Mask R-CNN to help with this understanding.
Framework and Model Analysis on Bengali Document Layout Analysis Dataset: BaDLAD
We looked at lots of different Bengali documents in our study.
Bridging the Performance Gap between DETR and R-CNN for Graphical Object Detection in Document Images
Upon integrating query modifications in the DETR, we outperform prior works and achieve new state-of-the-art results with the mAP of 96. 9\%, 95. 7\% and 99. 3\% on TableBank, PubLaynet, PubTables, respectively.
Document Layout Annotation: Database and Benchmark in the Domain of Public Affairs
Every day, thousands of digital documents are generated with useful information for companies, public organizations, and citizens.
M$^{6}$Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout Analysis
Document layout analysis is a crucial prerequisite for document understanding, including document retrieval and conversion.
Extracting Complex Named Entities in Legal Documents via Weakly Supervised Object Detection
Accurate Named Entity Recognition (NER) is crucial for various information retrieval tasks in industry.
Détection d'Objets dans les documents numérisés par réseaux de neurones profonds
For this purpose, we propose confidence estimators from different approaches for object detection.
Efficient few-shot learning for pixel-precise handwritten document layout analysis
Layout analysis is a task of uttermost importance in ancient handwritten document analysis and represents a fundamental step toward the simplification of subsequent tasks such as optical character recognition and automatic transcription.
Transformer-based Approach for Document Understanding
We present an end-to-end transformer-based framework named TRDLU for the task of Document Layout Understanding (DLU).
Unified Pretraining Framework for Document Understanding
Document intelligence automates the extraction of information from documents and supports many business applications.
