activity
20222025
most citedGraph Neural Networks and Representation Embedding for Table Extraction in PDF Documents

20 citations · 24 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2025

CoSMo: A Multimodal Transformer for Page Stream Segmentation in Comic Books

Marc Serra Ortega, Emanuele Vivoli, Artemis Llabrés +1

This paper introduces CoSMo, a novel multimodal Transformer for Page Stream Segmentation (PSS) in comic books, a critical task for automated content understanding, as it is a neces…

cs.CV2025★ 2 cited

ComicsPAP: understanding comic strips by picking the correct panel

Emanuele Vivoli, Artemis Llabrés, Mohamed Ali Souibgui +3

Large multimodal models (LMMs) have made impressive strides in image captioning, VQA, and video comprehension, yet they still struggle with the intricate temporal and spatial cues…

cs.CV2025

HoloMine: A Synthetic Dataset for Buried Landmines Recognition using Microwave Holographic Imaging

Emanuele Vivoli, Lorenzo Capineri, Marco Bertini

The detection and removal of landmines is a complex and risky task that requires advanced remote sensing techniques to reduce the risk for the professionals involved in this task.…

cs.CV2024

ComiCap: A VLMs pipeline for dense captioning of Comic Panels

Emanuele Vivoli, Niccolò Biondi, Marco Bertini +1

The comic domain is rapidly advancing with the development of single- and multi-page analysis and synthesis models. Recent benchmarks and datasets have been introduced to support a…

cs.CV2024★ 1 cited

Towards Generative Class Prompt Learning for Fine-grained Visual Recognition

Soumitri Chattopadhyay, Sanket Biswas, Emanuele Vivoli +1

Although foundational vision-language models (VLMs) have proven to be very successful for various semantic discrimination tasks, they still struggle to perform faithfully for fine-…

cs.CV2024

One missing piece in Vision and Language: A Survey on Comics Understanding

Emanuele Vivoli, Mohamed Ali Souibgui, Andrey Barsky +3

Vision-language models have recently evolved into versatile systems capable of high performance across a range of tasks, such as document understanding, visual question answering,…

cs.CV2024

Comics Datasets Framework: Mix of Comics datasets for detection benchmarking

Emanuele Vivoli, Irene Campaioli, Mariateresa Nardoni +3

Comics, as a medium, uniquely combine text and images in styles often distinct from real-world visuals. For the past three decades, computational research on comics has evolved fro…

cs.CV2024

CoMix: A Comprehensive Benchmark for Multi-Task Comic Understanding

Emanuele Vivoli, Marco Bertini, Dimosthenis Karatzas

The comic domain is rapidly advancing with the development of single-page analysis and synthesis models. However, evaluation metrics and datasets lag behind, often limited to small…

cs.CV2024

Multimodal Transformer for Comics Text-Cloze

Emanuele Vivoli, Joan Lafuente Baeza, Ernest Valveny Llobet +1

This work explores a closure task in comics, a medium where visual and textual elements are intricately intertwined. Specifically, Text-cloze refers to the task of selecting the co…

eess.IV2023

Error assessment of microwave holography inversion for shallow buried objects

Emanuele Vivoli, Luca Bossi, Marco Bertini +2

Holographic imaging is a technique that uses microwave energy to create a three-dimensional image of an object or scene. This technology has potential applications in land mine det…

cs.CL2023

CTE: A Dataset for Contextualized Table Extraction

Andrea Gemelli, Emanuele Vivoli, Simone Marinai

Relevant information in documents is often summarized in tables, helping the reader to identify useful facts. Most benchmark datasets support either document layout analysis or tab…

cs.CV2022★ 1 cited

MUST-VQA: MUltilingual Scene-text VQA

Emanuele Vivoli, Ali Furkan Biten, Andres Mafla +2

In this paper, we present a framework for Multilingual Scene Text Visual Question Answering that deals with new languages in a zero-shot fashion. Specifically, we consider the task…

cs.CV2022★ 20 cited

Graph Neural Networks and Representation Embedding for Table Extraction in PDF Documents

Andrea Gemelli, Emanuele Vivoli, Simone Marinai

Tables are widely used in several types of documents since they can bring important information in a structured way. In scientific papers, tables can sum up novel discoveries and s…