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20202026
most citedFocus on Impact: Indoor Exploration with Intrinsic Motivation

22 citations · 62 across the 29 of their papers we have counts for

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28 papers · 1 filter

cs.CV2026

Editing Everything Everywhere All at Once

Fabio Quattrini, Carmine Zaccagnino, Enis Simsar +4

Editing multiple elements of an image in a single forward pass is a practical alternative to multi-turn image manipulation, offering improved efficiency and potentially better harm…

cs.CV2026

A Text Recognition Dataset from Sahidic Coptic Ancient Manuscripts

Fabio Quattrini, Carmine Zaccagnino, Costanza Bianchi +2

In this work, we target Handwritten Text Recognition (HTR) in low-resource scenarios, which arise from underrepresented languages, rare scripts, and degraded visual conditions typi…

cs.CV2026

Zero-Shot Synthetic-to-Real Handwritten Text Recognition via Task Analogies

Carlos Garrido-Munoz, Aniello Panariello, Silvia Cascianelli +4

Handwritten Text Recognition (HTR) models trained on synthetic handwriting often struggle to generalize to real text, and existing adaptation methods still require real samples fro…

cs.CV2026

Shifting the Breaking Point of Flow Matching for Multi-Instance Editing

Carmine Zaccagnino, Fabio Quattrini, Enis Simsar +4

Flow matching models have recently emerged as an efficient alternative to diffusion, especially for text-guided image generation and editing, offering faster inference through cont…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025★ 1 cited

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…

cs.CV2025

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,…

cs.CV2024

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…

cs.CV2024

μgat: Improving Single-Page Document Parsing by Providing Multi-Page Context

Fabio Quattrini, Carmine Zaccagnino, Silvia Cascianelli +2

Regesta are catalogs of summaries of other documents and, in some cases, are the only source of information about the content of such full-length documents. For this reason, they a…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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,…

cs.CV2023★ 1 cited

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…

cs.CV2023

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…

cs.CV2023

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…

cs.CV2023

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…

cs.CV2023★ 1 cited

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…

cs.CV2022

Boosting Modern and Historical Handwritten Text Recognition with Deformable Convolutions

Silvia Cascianelli, Marcella Cornia, Lorenzo Baraldi +1

Handwritten Text Recognition (HTR) in free-layout pages is a challenging image understanding task that can provide a relevant boost to the digitization of handwritten documents and…

cs.CV2022

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…

cs.CV2022★ 3 cited

Embodied Navigation at the Art Gallery

Roberto Bigazzi, Federico Landi, Silvia Cascianelli +3

Embodied agents, trained to explore and navigate indoor photorealistic environments, have achieved impressive results on standard datasets and benchmarks. So far, experiments and e…

cs.CV2022★ 3 cited

Spot the Difference: A Novel Task for Embodied Agents in Changing Environments

Federico Landi, Roberto Bigazzi, Marcella Cornia +3

Embodied AI is a recent research area that aims at creating intelligent agents that can move and operate inside an environment. Existing approaches in this field demand the agents…

cs.CV2022★ 2 cited

CaMEL: Mean Teacher Learning for Image Captioning

Manuele Barraco, Matteo Stefanini, Marcella Cornia +3

Describing images in natural language is a fundamental step towards the automatic modeling of connections between the visual and textual modalities. In this paper we present CaMEL,…