67 citations · 68 across the 4 of their papers we have counts for
9 papers · 1 filter
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…
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…
Shape2.5D: A Dataset of Texture-less Surfaces for Depth and Normals Estimation
Muhammad Saif Ullah Khan, Sankalp Sinha, Didier Stricker +2
Reconstructing texture-less surfaces poses unique challenges in computer vision, primarily due to the lack of specialized datasets that cater to the nuanced needs of depth and norm…