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Papers Document Enhancement

“Document Enhancement” 태그가 달린 논문 13편 · 필터 해제

High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformer

2024-10-30 · Mingxian Li, Hao Sun, Yingtie Lei, Xiaofeng Zhang 외

Document images are often degraded by various stains, significantly impacting their readability and hindering downstream applications such as document digitization and analysis. The absence of a comprehensive stained doc…

Document EnhancementFeature ImportanceImage EnhancementImage Restoration

RealitySummary: Exploring On-Demand Mixed Reality Text Summarization and Question Answering using Large Language Models

2024-05-28 · Aditya Gunturu, Shivesh Jadon, Nandi Zhang, Morteza Faraji 외

Large Language Models (LLMs) are gaining popularity as tools for reading and summarization aids. However, little is known about their potential benefits when integrated with mixed reality (MR) interfaces to support every…

Document EnhancementMixed RealityOptical Character Recognition (OCR)Question Answering+1

NAF-DPM: A Nonlinear Activation-Free Diffusion Probabilistic Model for Document Enhancement

2024-04-08 · Giordano Cicchetti, Danilo Comminiello

Real-world documents may suffer various forms of degradation, often resulting in lower accuracy in optical character recognition (OCR) systems. Therefore, a crucial preprocessing step is essential to eliminate noise whil…

BinarizationDocument EnhancementOptical Character RecognitionOptical Character Recognition (OCR)

DECDM: Document Enhancement using Cycle-Consistent Diffusion Models

2023-11-16 · Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das 외

The performance of optical character recognition (OCR) heavily relies on document image quality, which is crucial for automatic document processing and document intelligence. However, most existing document enhancement m…

Data AugmentationDenoisingDocument EnhancementOptical Character Recognition+3

DocDiff: Document Enhancement via Residual Diffusion Models

2023-05-06 · Zongyuan Yang, Baolin Liu, Yongping Xiong, Lan Yi 외

Removing degradation from document images not only improves their visual quality and readability, but also enhances the performance of numerous automated document analysis and recognition tasks. However, existing regress…

DeblurringDenoisingDocument Enhancement

LP-IOANet: Efficient High Resolution Document Shadow Removal

2023-03-22 · Konstantinos Georgiadis, M. Kerim Yucel, Evangelos Skartados, Valia Dimaridou 외

Document shadow removal is an integral task in document enhancement pipelines, as it improves visibility, readability and thus the overall quality. Assuming that the majority of practical document shadow removal scenario…

Document EnhancementDocument Shadow RemovalShadow RemovalVocal Bursts Intensity Prediction

Text-DIAE: A Self-Supervised Degradation Invariant Autoencoders for Text Recognition and Document Enhancement

2022-03-09 · Mohamed Ali Souibgui, Sanket Biswas, Andres Mafla, Ali Furkan Biten 외

In this paper, we propose a Text-Degradation Invariant Auto Encoder (Text-DIAE), a self-supervised model designed to tackle two tasks, text recognition (handwritten or scene-text) and document image enhancement. We start…

Document EnhancementImage EnhancementScene Text Recognition

Evaluating Deep Neural Networks for Image Document Enhancement

2021-06-11 · Lucas N. Kirsten, Ricardo Piccoli, Ricardo Ribani

This work evaluates six state-of-the-art deep neural network (DNN) architectures applied to the problem of enhancing camera-captured document images. The results from each network were evaluated both qualitatively and qu…

Deep LearningDocument EnhancementImage EnhancementImage Quality Assessment

Light-weight Document Image Cleanup using Perceptual Loss

2021-05-19 · Soumyadeep Dey, Pratik Jawanpuria

Smartphones have enabled effortless capturing and sharing of documents in digital form. The documents, however, often undergo various types of degradation due to aging, stains, or shortcoming of capturing environment suc…

DecoderDocument EnhancementTransfer Learning

DE-GAN: A Conditional Generative Adversarial Network for Document Enhancement

2020-10-17 · Mohamed Ali Souibgui, Yousri Kessentini

Documents often exhibit various forms of degradation, which make it hard to be read and substantially deteriorate the performance of an OCR system. In this paper, we propose an effective end-to-end framework named Docume…

BinarizationDeblurringDocument EnhancementGenerative Adversarial Network+1

Document Enhancement System Using Auto-encoders

2019-09-14 · NeurIPS Workshop Document_Intelligen 2019 12 · Mehrdad J. Gangeh, Sunil R. Tiyyagura, Sridhar V. Dasaratha, Hamid Motahari 외

The conversion of scanned documents to digital forms is performed using an Optical Character Recognition (OCR) software. This work focuses on improving the quality of scanned documents in order to improve the OCR output.…

DenoisingDocument EnhancementOptical Character RecognitionOptical Character Recognition (OCR)

DeepOtsu: Document Enhancement and Binarization using Iterative Deep Learning

2019-01-18 · Sheng He, Lambert Schomaker

This paper presents a novel iterative deep learning framework and apply it for document enhancement and binarization. Unlike the traditional methods which predict the binary label of each pixel on the input image, we tra…

BinarizationDeep LearningDocument Enhancement

Document Enhancement Using Visibility Detection

2018-06-01 · CVPR 2018 6 · Netanel Kligler, Sagi Katz, Ayellet Tal

This paper re-visits classical problems in document enhancement. Rather than proposing a new algorithm for a specific problem, we introduce a novel general approach. The key idea is to modify any state- of-the-art algori…

BinarizationDocument EnhancementDocument Shadow Removal
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