1 citations · 3 across the 14 of their papers we have counts for
14 papers
Autoregressive Styled Text Image Generation, but Make it Reliable
Carmine Zaccagnino, Fabio Quattrini, Vittorio Pippi +3
Generating faithful and readable styled text images (especially for Styled Handwritten Text generation - HTG) is an open problem with several possible applications across graphic d…
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…
Zero-Shot Styled Text Image Generation, but Make It Autoregressive
Vittorio Pippi, Fabio Quattrini, Silvia Cascianelli +2
Styled Handwritten Text Generation (HTG) has recently received attention from the computer vision and document analysis communities, which have developed several solutions, either…
ToFu: Visual Tokens Reduction via Fusion for Multi-modal, Multi-patch, Multi-image Task
Vittorio Pippi, Matthieu Guillaumin, Silvia Cascianelli +3
Large Multimodal Models (LMMs) are powerful tools that are capable of reasoning and understanding multimodal information beyond text and language. Despite their entrenched impact,…
Merging and Splitting Diffusion Paths for Semantically Coherent Panoramas
Fabio Quattrini, Vittorio Pippi, Silvia Cascianelli +1
Diffusion models have become the State-of-the-Art for text-to-image generation, and increasing research effort has been dedicated to adapting the inference process of pretrained di…
Alfie: Democratising RGBA Image Generation With No $$$
Fabio Quattrini, Vittorio Pippi, Silvia Cascianelli +1
Designs and artworks are ubiquitous across various creative fields, requiring graphic design skills and dedicated software to create compositions that include many graphical elemen…
Binarizing Documents by Leveraging both Space and Frequency
Fabio Quattrini, Vittorio Pippi, Silvia Cascianelli +1
Document Image Binarization is a well-known problem in Document Analysis and Computer Vision, although it is far from being solved. One of the main challenges of this task is that…
VATr++: Choose Your Words Wisely for Handwritten Text Generation
Bram Vanherle, Vittorio Pippi, Silvia Cascianelli +3
Styled Handwritten Text Generation (HTG) has received significant attention in recent years, propelled by the success of learning-based solutions employing GANs, Transformers, and,…
HWD: A Novel Evaluation Score for Styled Handwritten Text Generation
Vittorio Pippi, Fabio Quattrini, Silvia Cascianelli +1
Styled Handwritten Text Generation (Styled HTG) is an important task in document analysis, aiming to generate text images with the handwriting of given reference images. In recent…
Volumetric Fast Fourier Convolution for Detecting Ink on the Carbonized Herculaneum Papyri
Fabio Quattrini, Vittorio Pippi, Silvia Cascianelli +1
Recent advancements in Digital Document Restoration (DDR) have led to significant breakthroughs in analyzing highly damaged written artifacts. Among those, there has been an increa…
How to Choose Pretrained Handwriting Recognition Models for Single Writer Fine-Tuning
Vittorio Pippi, Silvia Cascianelli, Christopher Kermorvant +1
Recent advancements in Deep Learning-based Handwritten Text Recognition (HTR) have led to models with remarkable performance on both modern and historical manuscripts in large benc…
Evaluating Synthetic Pre-Training for Handwriting Processing Tasks
Vittorio Pippi, Silvia Cascianelli, Lorenzo Baraldi +1
In this work, we explore massive pre-training on synthetic word images for enhancing the performance on four benchmark downstream handwriting analysis tasks. To this end, we build…
Handwritten Text Generation from Visual Archetypes
Vittorio Pippi, Silvia Cascianelli, Rita Cucchiara
Generating synthetic images of handwritten text in a writer-specific style is a challenging task, especially in the case of unseen styles and new words, and even more when these la…
The LAM Dataset: A Novel Benchmark for Line-Level Handwritten Text Recognition
Silvia Cascianelli, Vittorio Pippi, Martin Maarand +4
Handwritten Text Recognition (HTR) is an open problem at the intersection of Computer Vision and Natural Language Processing. The main challenges, when dealing with historical manu…