DocEnTr: An End-to-End Document Image Enhancement Transformer
Computer Vision Center Universitat Autònoma de Barcelona（巴塞罗那自治大学计算机视觉中心）；Digital Research Center of Sfax（斯法克斯数字研究中心）；University of Sfax（斯法克斯大学）；Indian Statistical Institute（印度统计研究所）
Mohamed Ali Souibgui, Sanket Biswas, Sana Khamekhem Jemni, Yousri Kessentini, Alicia Fornés, Josep Lladós, Umapada Pal
Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for proper usage. To address this challenge, we present a new encoder-decoder architecture based on vision transformers to enhance both machine-printed and handwritten document images, in an end-to-end fashion. The encoder operates directly on the pixel patches with their positional information without the use of any convolutional layers, while the decoder reconstructs a clean image from the encoded patches. Conducted experiments show a superiority of the proposed model compared to the state-of the-art methods on several DIBCO benchmarks. Code and models will be publicly available at: \url{https://github.com/dali92002/DocEnTR}.
MFE-GAN: Efficient GAN-based Framework for Document Image Enhancement and Binarization with Multi-scale Feature Extraction
Graduate School of Informatics, Kyoto University（京都大学信息科学研究生院）；School of Information Technology, Monash University Malaysia（墨尔本大学马来西亚分校信息科技学院）；Department of Electrical and Computer Engineering, Rice University（Rice大学电气与计算机工程系）；Department of Electrical and Computer Engineering, Tamkang University（Tamkang大学电气与计算机工程系）
Q-Doc: Benchmarking Document Image Quality Assessment Capabilities in Multi-modal Large Language Models
South China Normal University（华南师范大学）；Nanyang Technological University（南洋理工大学）；City University of Hong Kong（香港城市大学）；Shenzhen Academy of Inspection and Quarantine（深圳检验检疫局）；Shenzhen University（深圳大学）
Efficient Generative Adversarial Networks for Color Document Image Enhancement and Binarization Using Multi-scale Feature Extraction
Graduate Institute of Networking and Multimedia, National Taiwan University（国立台湾大学网络与多媒体研究所）；School of Information Technolog, Monash University Malaysia（莫纳什大学马来西亚分校信息科技学院）；Department of Electrical and Computer Engineering, Tamkang University（Tamkang大学电子与计算机工程系）
Beyond pixels and regions: A non local patch means (NLPM) method for content-level restoration, enhancement, and reconstruction of degraded document images
VERSE: Visual Embedding Reduction and Space Exploration. Clustering-Guided Insights for Training Data Enhancement in Visually-Rich Document Understanding
Institute for Research in Technology, ICAI School of Engineering, Comillas Pontifical University（技术研究所、ICAI工程学院、科利马斯天主教大学）
Two-stage generative adversarial networks for document image binarization with color noise and background removal
Korea Institute of Science and Technology Europe Forschungsgesellschaft mbH（韩国科学技术研究院欧洲研究所）；TU Kaiserslautern（凯泽斯劳滕工业大学）；Kyung Hee University（庆熙大学）；German Research Center for Artificial Intelligence (DFKI)（德国人工智能研究中心）
A Comparative Study of Filtering Approaches Applied to Color Archival Document Images
Sousse University, National Engineering School of Sousse（苏塞大学，苏塞国家工程学院）；LATIS - Laboratory of Advanced Technology and Intelligent Systems（先进技术与智能系统实验室（LATIS））
High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformer
School of Computer Science and Engineering, Huizhou University（惠州学院计算机科学与工程学院）；Faculty of Science and Technology, University of Macau（澳门大学科技学院）；School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University（上海交通大学电子信息与电气工程学院）；Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；School of Electronic and Communication Engineering, Shenzhen Polytechnic University（深圳职业技术学院电子与通信工程学院）
DocShaDiffusion: Diffusion Model in Latent Space for Document Image Shadow Removal
School of Software, Northwestern Polytechnical University（软件学院，西北工业大学）；School of Computer Science and Engineering, South China University of Technology and Pazhou Lab（计算机科学与工程学院，华南理工大学及琶洲实验室）
Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networks
Graduate Institute of Networking and Multimedia, National Taiwan University（国立台湾大学网络与多媒体研究所）；Department of Electrical and Computer Engineering, Tamkang University（潭府大学电子工程系）；Department of Electrical and Computer Engineering, Rice University（里德大学电子工程系）
Bridging the Performance Gap between DETR and R-CNN for Graphical Object Detection in Document Images
Technical University of Kaiserslautern（凯泽斯劳滕工业大学）；German Research Institute for Artificial Intelligence (DFKI)（德国人工智能研究中心）；Luleå University of Technology（吕勒奥理工大学）
Towards End-to-End Semi-Supervised Table Detection with Semantic Aligned Matching Transformer
Technical University of Kaiserslautern（凯泽斯劳滕工业大学）；Mindgarage, Technical University of Kaiserslautern（凯泽斯劳滕工业大学Mindgarage）；German Research Institute for Artificial Intelligence (DFKI)（德国人工智能研究中心（DFKI））
Benchmarking OCR Pipelines with Adaptive Enhancement for Multi-Domain Retail Bill Digitization
Data Analytics Team Lead, JP Research India Pvt. Ltd.（JP Research India Pvt. Ltd. 数据分析团队负责人）；PhD Scholar, Business Analytics and Information Technology（Business Analytics and Information Technology 博士学者）
