Finished papers

[chahyon-ku]

Survey

• A Survey of Deep Learning Approaches for OCR and Document Understanding (https://arxiv.org/abs/2011.13534)

[chahyon-ku]

Instance Segmentation

• Fully Convolutional Networks for Semantic Segmentation (https://arxiv.org/abs/1411.4038)

[chahyon-ku]

Object Detection

• Scalable Object Detection using Deep Neural Networks (https://www.arxiv-vanity.com/papers/1312.2249/)
• SSD: Single Shot MultiBox Detector (https://www.arxiv-vanity.com/papers/1512.02325/)
• You Only Look Once: Unified, Real-Time Object Detection (https://arxiv.org/abs/1506.02640)

[chahyon-ku]

Data Generation

• Synthetic Data for Text Localisation in Natural Images (https://www.arxiv-vanity.com/papers/1604.06646/)
• TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text (https://www.arxiv-vanity.com/papers/2105.05486/)

[chahyon-ku]

OCR/Document Understanding

• Tesseract Technical Documentation (https://tesseract-ocr.github.io/tessdoc/tess3/Technical-Documentation.html)
• Textboxes: a fast text detector with a single deep neural network (https://arxiv.org/abs/1611.06779)
• Donut: Document Understanding Transformer without OCR (https://arxiv.org/abs/2111.15664)