SOTAVerified

Document Layout Analysis

"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

Papers

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Showing 1–50 of 99 papers

TitleStatusHype
PP-DocLayout: A Unified Document Layout Detection Model to Accelerate Large-Scale Data ConstructionCode9
DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive PerceptionCode9
DocLayNet: A Large Human-Annotated Dataset for Document-Layout AnalysisCode8
A Large Dataset of Historical Japanese Documents with Complex LayoutsCode3
PubLayNet: largest dataset ever for document layout analysisCode2
UniHDSA: A Unified Relation Prediction Approach for Hierarchical Document Structure AnalysisCode2
BEiT: BERT Pre-Training of Image TransformersCode2
LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingCode2
Towards End-to-End Unified Scene Text Detection and Layout AnalysisCode2
Detect-Order-Construct: A Tree Construction based Approach for Hierarchical Document Structure AnalysisCode2
CTE: A Dataset for Contextualized Table ExtractionCode1
DiT: Self-supervised Pre-training for Document Image TransformerCode1
Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural NetworksCode1
DocBank: A Benchmark Dataset for Document Layout AnalysisCode1
CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document ImagesCode1
docExtractor: An off-the-shelf historical document element extractionCode1
Doc-GCN: Heterogeneous Graph Convolutional Networks for Document Layout AnalysisCode1
M6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout AnalysisCode1
DocSegTr: An Instance-Level End-to-End Document Image Segmentation TransformerCode1
PARAGRAPH2GRAPH: A GNN-based framework for layout paragraph analysisCode1
DocSynth: A Layout Guided Approach for Controllable Document Image SynthesisCode1
Document AI: A Comparative Study of Transformer-Based, Graph-Based Models, and Convolutional Neural Networks For Document Layout AnalysisCode1
RoDLA: Benchmarking the Robustness of Document Layout Analysis ModelsCode1
Combining Visual and Textual Features for Semantic Segmentation of Historical NewspapersCode1
SelfDocSeg: A Self-Supervised vision-based Approach towards Document SegmentationCode1
appjsonify: An Academic Paper PDF-to-JSON Conversion ToolkitCode1
Training data-efficient image transformers & distillation through attentionCode1
DANIEL: A fast Document Attention Network for Information Extraction and Labelling of handwritten documentsCode1
DocXChain: A Powerful Open-Source Toolchain for Document Parsing and BeyondCode0
Vision Grid Transformer for Document Layout AnalysisCode0
ICDAR 2021 Competition on Historical Map SegmentationCode0
SFDLA: Source-Free Document Layout AnalysisCode0
Text Role Classification in Scientific Charts Using Multimodal TransformersCode0
dhSegment: A generic deep-learning approach for document segmentationCode0
LayoutLMv3: Pre-training for Document AI with Unified Text and Image MaskingCode0
BaDLAD: A Large Multi-Domain Bengali Document Layout Analysis DatasetCode0
VSR: A Unified Framework for Document Layout Analysis combining Vision, Semantics and RelationsCode0
A Graphical Approach to Document Layout AnalysisCode0
Multimodal weighted graph representation for information extraction from visually rich documents.Code0
Multi-Task Handwritten Document Layout AnalysisCode0
M^6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout AnalysisCode0
Class-Agnostic Region-of-Interest Matching in Document ImagesCode0
DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense UnderstandingCode0
LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document UnderstandingCode0
Information Extraction from Visually Rich Documents Using Directed Weighted Graph Neural NetworkCode0
PdfTable: A Unified Toolkit for Deep Learning-Based Table ExtractionCode0
Document Layout Annotation: Database and Benchmark in the Domain of Public AffairsCode0
LayoutReader: Pre-training of Text and Layout for Reading Order DetectionCode0
Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks—0
Visual Detection with Context for Document Layout Analysis—0
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All datasetsPubLayNet valU-DIADS-BibD4LADocument Layout Recognition Challenge mini-devDocument Layout Recognition Challenge testRVL-CDIP

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CDeC-NetTable0.98—Unverified
2VGTOverall0.96—Unverified
3TRDLUOverall0.96—Unverified
4VSROverall0.96—Unverified
5DETROverall0.96—Unverified
6LayoutLMv3-BOverall0.95—Unverified
7DiT-LOverall0.95—Unverified
8DoPTAOverall0.95—Unverified
9UDocOverall0.94—Unverified
10ResNext-101-32×8dOverall0.94—Unverified
#ModelMetricClaimedVerifiedStatus
1CV-GroupClass Average IoU83.4—Unverified
2CNKIClass Average IoU77.8—Unverified
3VAI-OCRClass Average IoU70.7—Unverified
4DeepLabV3+Class Average IoU66.5—Unverified
5L3i++Class Average IoU (Few-shot setting)61.1—Unverified
#ModelMetricClaimedVerifiedStatus
1DoPTA mAP70.72—Unverified
2DocLayout-YOLO mAP70.3—Unverified
3VGT mAP68.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Faster_RCNNOverall0.96—Unverified
2fglihaiOverall0.96—Unverified
3Faster-RCNNOverall0.95—Unverified
#ModelMetricClaimedVerifiedStatus
1fglihaiOverall0.92—Unverified
2USYD NLP_CS29-2Overall0.92—Unverified
3Faster-RCNNOverall0.91—Unverified
#ModelMetricClaimedVerifiedStatus
1VisualWordGridFAR28.7—Unverified