Papers with Code 아카이브
Table Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/DevashishPrasad/CascadeTabNet
공식 코드https://github.com/Psarpei/Multi-Type-TD-TSR
공식 코드https://github.com/abdoelsayed2016/TNCR_Dataset
공식 코드https://github.com/abdoelsayed2016/table-detection-structure-recognition
공식 코드Deep learning for table detection and structure recognition: A survey
https://github.com/ailab-unifi/cte-dataset
공식 코드https://github.com/andreagemelli/doc2graph
공식 코드Doc2Graph: a Task Agnostic Document Understanding Framework based on Graph Neural Networks
https://github.com/doc-analysis/TableBank
공식 코드TableBank: A Benchmark Dataset for Table Detection and Recognition
https://github.com/holms-ur/fine-tuning
공식 코드The Benefits of Close-Domain Fine-Tuning for Table Detection in Document Images
https://github.com/maxkinny/tabrecset
공식 코드A large-scale dataset for end-to-end table recognition in the wild
https://github.com/mdv3101/CDeCNet
공식 코드CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images
https://github.com/microsoft/TableSense
공식 코드TableSense: Spreadsheet Table Detection with Convolutional Neural Networks
https://github.com/microsoft/comphrdoc
공식 코드UniHDSA: A Unified Relation Prediction Approach for Hierarchical Document Structure Analysis
https://github.com/microsoft/table-transformer
공식 코드PubTables-1M: Towards comprehensive table extraction from unstructured documents
https://github.com/microsoft/unilm/tree/master/dit
공식 코드DiT: Self-supervised Pre-training for Document Image Transformer
https://github.com/mnamysl/table-interpretation
공식 코드Flexible Table Recognition and Semantic Interpretation System
https://github.com/nikolamilosevic86/TabInOut
공식 코드A framework for information extraction from tables in biomedical literature
https://github.com/sap-samples/clustertabnet
공식 코드ClusterTabNet: Supervised clustering method for table detection and table structure recognition
https://github.com/uobinxiao/SparseTableDet
공식 코드https://github.com/zhaowc-ustc/tabpedia
공식 코드TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy
https://github.com/2023-MindSpore-4/Code2/tree/main/DDAG
CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images
https://github.com/Darthholi/DocumentConcepts
https://github.com/MindCode-4/code-3/tree/main/deit
DiT: Self-supervised Pre-training for Document Image Transformer
https://github.com/RajArPatra/Super-OCR
https://github.com/abdoelsayed2016/tncr
Deep learning for table detection and structure recognition: A survey
https://github.com/asagar60/TableNet-pytorch
https://github.com/doc-analysis/DocBank
TableBank: A Benchmark Dataset for Table Detection and Recognition
https://github.com/green93/TableNet-Deep-Learning-model-for-Tabular-Data-Extraction-from-Scanned-Document-Image
https://github.com/hmnth1/table_ocr
https://github.com/huggingface/transformers
DiT: Self-supervised Pre-training for Document Image Transformer
https://github.com/microsoft/TUTA_table_understanding
SpreadsheetLLM: Encoding Spreadsheets for Large Language Models
https://github.com/microsoft/hitab
SpreadsheetLLM: Encoding Spreadsheets for Large Language Models
https://github.com/phamquiluan/table-transformer
PubTables-1M: Towards comprehensive table extraction from unstructured documents
https://github.com/samarthramesh/CDeC-Net
CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images
https://github.com/shrikumaran/ABInBev-Hackathon
https://github.com/subex/STDW
Table Detection in the Wild: A Novel Diverse Table Detection Dataset and Method
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.