https://github.com/PaddlePaddle/PaddleNLP/tree/develop/paddlenlp/transformers/layoutxlm
LayoutXLM: Multimodal Pre-training for Multilingual Visually-rich Document Understanding
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Document AI
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/PierreSenellart/theoremkb
https://github.com/RajArPatra/Super-OCR
A Survey of Deep Learning Approaches for OCR and Document Understanding
https://github.com/Tixierae/gow_tools
Message Passing Attention Networks for Document Understanding
https://github.com/Ucas-HaoranWei/Vary
Focus Anywhere for Fine-grained Multi-page Document Understanding
https://github.com/abhijeet3922/vision-RAG
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/adlnlp/Chulo
ChuLo: Chunk-Level Key Information Representation for Long Document Processing
https://github.com/antoinedelplace/chargrid
https://github.com/bobxwu/topmost
On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling
https://github.com/code-implementation1/Code9/tree/main/OCRNet
https://github.com/cydal/LayoutML_pytorch
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/doc-analysis/DocBank
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/doc-doc/NExT-OE
PaLI-X: On Scaling up a Multilingual Vision and Language Model
https://github.com/ds4sd/deepsearch-toolkit
Delivering Document Conversion as a Cloud Service with High Throughput and Responsiveness
https://github.com/facebookresearch/data2vec_vision
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/herobd/NAF_dataset
End-to-end Document Recognition and Understanding with Dessurt
https://github.com/huggingface/transformers
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/illuin-tech/colpali
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/illuin-tech/grouse
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/illuin-tech/vidore-benchmark
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/impira/docquery
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/infly-ai/inf-mllm
Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document Parsing
https://github.com/kenAlparslan/Texttract
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/kyegomez/PALI
PaLI-X: On Scaling up a Multilingual Vision and Language Model
https://github.com/likaixin2000/screenspot-pro-gui-grounding
https://github.com/littletomatodonkey/Augment-XY-CUT
XYLayoutLM: Towards Layout-Aware Multimodal Networks For Visually-Rich Document Understanding
https://github.com/lulia0228/Document_IE
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/mayubo2333/mmlongbench-doc
MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizations
https://github.com/microsoft/unilm/tree/master/layoutlm
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/nunenuh/layoutlm.pytorch
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/omarsou/layoutlm_CORD
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/opendatalab/PDF-Extract-Kit
https://github.com/princeton-nlp/CharXiv
https://github.com/pwc-1/Paper-10
Unifying Vision, Text, and Layout for Universal Document Processing
https://github.com/pwc-1/Paper-9/tree/main/layoutlm
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/pwc-1/Paper-9/tree/main/layoutlmv2
LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.