8 citations · 12 across the 9 of their papers we have counts for
9 papers
Are Euler angles a useful rotation parameterisation for pose estimation with Normalizing Flows?
Giorgos Sfikas, Konstantina Nikolaidou, Foteini Papadopoulou +2
Object pose estimation is a task that is of central importance in 3D Computer Vision. Given a target image and a canonical pose, a single point estimate may very often be sufficien…
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…
DiffusionPen: Towards Controlling the Style of Handwritten Text Generation
Konstantina Nikolaidou, George Retsinas, Giorgos Sfikas +1
Handwritten Text Generation (HTG) conditioned on text and style is a challenging task due to the variability of inter-user characteristics and the unlimited combinations of charact…
Rethinking HTG Evaluation: Bridging Generation and Recognition
Konstantina Nikolaidou, George Retsinas, Giorgos Sfikas +1
The evaluation of generative models for natural image tasks has been extensively studied. Similar protocols and metrics are used in cases with unique particularities, such as Handw…
WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models
Konstantina Nikolaidou, George Retsinas, Vincent Christlein +5
Text-to-Image synthesis is the task of generating an image according to a specific text description. Generative Adversarial Networks have been considered the standard method for im…
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning Conventions
Gustav Grund Pihlgren, Konstantina Nikolaidou, Prakash Chandra Chhipa +4
In recent years, deep perceptual loss has been widely and successfully used to train machine learning models for many computer vision tasks, including image synthesis, segmentation…
A Survey of Historical Document Image Datasets
Konstantina Nikolaidou, Mathias Seuret, Hamam Mokayed +1
This paper presents a systematic literature review of image datasets for document image analysis, focusing on historical documents, such as handwritten manuscripts and early prints…
Potential Idiomatic Expression (PIE)-English: Corpus for Classes of Idioms
Tosin P. Adewumi, Roshanak Vadoodi, Aparajita Tripathy +3
We present a fairly large, Potential Idiomatic Expression (PIE) dataset for Natural Language Processing (NLP) in English. The challenges with NLP systems with regards to tasks such…