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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 99 papers

TitleStatusHype
CTE: A Dataset for Contextualized Table ExtractionCode1
Détection d'Objets dans les documents numérisés par réseaux de neurones profonds—0
M6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout AnalysisCode1
Efficient few-shot learning for pixel-precise handwritten document layout analysis—0
Transformer-based Approach for Document Understanding—0
Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural NetworksCode1
Doc-GCN: Heterogeneous Graph Convolutional Networks for Document Layout AnalysisCode1
DocLayNet: A Large Human-Annotated Dataset for Document-Layout AnalysisCode8
Unified Pretraining Framework for Document Understanding—0
LayoutLMv3: Pre-training for Document AI with Unified Text and Image MaskingCode0
Neural Graph Matching for Modification Similarity Applied to Electronic Document Comparison—0
Towards End-to-End Unified Scene Text Detection and Layout AnalysisCode2
DiT: Self-supervised Pre-training for Document Image TransformerCode1
DocBed: A Multi-Stage OCR Solution for Documents with Complex Layouts—0
DocSegTr: An Instance-Level End-to-End Document Image Segmentation TransformerCode1
Cross-Domain Document Layout Analysis Using Document Style Guide—0
Document Layout Analysis with Aesthetic-Guided Image Augmentation—0
Document AI: Benchmarks, Models and Applications—0
Document Image Layout Analysis via Explicit Edge Embedding Network—0
LayoutReader: Pre-training of Text and Layout for Reading Order DetectionCode0
VTLayout: Fusion of Visual and Text Features for Document Layout Analysis—0
Human-In-The-Loop Document Layout Analysis—0
DocSynth: A Layout Guided Approach for Controllable Document Image SynthesisCode1
Evaluation of a Region Proposal Architecture for Multi-task Document Layout Analysis—0
BEiT: BERT Pre-Training of Image TransformersCode2
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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