7 papers
Performance Gap Analysis between Latin and Arabic Scripts HTR
Sana Al-azzawi, Elisa Barney, Marcus Liwicki
Recent studies have shown that handwritten text recognition (HTR) systems perform worse on Arabic-script datasets than on Latin-script data. However, the reasons for this gap are s…
Cross-Lingual Learning within Arabic Script for Low-Resource HTR
Sana Al-azzawi, Elisa Barney, Marcus Liwicki
Handwritten Text Recognition (HTR) with limited labeled data remains a challenging problem, particularly for Arabic-script languages. Although modern sequence-based recognizers per…
SemAttNet: Towards Attention-based Semantic Aware Guided Depth Completion
Danish Nazir, Marcus Liwicki, Didier Stricker +1
Depth completion involves recovering a dense depth map from a sparse map and an RGB image. Recent approaches focus on utilizing color images as guidance images to recover depth at…
Inhibitor Transformers and Gated RNNs for Torus Efficient Fully Homomorphic Encryption
Rickard Brännvall, Tony Zhang, Henrik Forsgren +3
This paper introduces efficient modifications to neural network-based sequence processing approaches, laying new grounds for scalable privacy-preserving machine learning under Full…
Dual Orthogonal Guidance for Robust Diffusion-based Handwritten Text Generation
Konstantina Nikolaidou, George Retsinas, Giorgos Sfikas +3
Diffusion-based Handwritten Text Generation (HTG) approaches achieve impressive results on frequent, in-vocabulary words observed at training time and on regular styles. However, t…
Quo Vadis Handwritten Text Generation for Handwritten Text Recognition?
Vittorio Pippi, Konstantina Nikolaidou, Silvia Cascianelli +4
The digitization of historical manuscripts presents significant challenges for Handwritten Text Recognition (HTR) systems, particularly when dealing with small, author-specific col…