Nicola Fanelli
I am a PhD student in Computer Science & Mathematics in the Department of
Computer Science at the University of Bari Aldo
Moro, where I work on computer vision and deep learning, under the
supervision of Prof.
Giovanna Castellano and Prof. Gennaro
Vessio.
I am currently pursuing a PhD funded by a PhD fellowship within the
framework of the Italian "D.M. n. 118/23" under the PNRR, Mission 4, Component 1,
Investment 4.1 on the PhD project "Analysis and Valorization of Digitized
Artistic Heritage using Artificial Intelligence techniques". I am currently working
in the CILab lab.
In 2023, I obtained my Master's degree in Computer Science (AI curriculum) from the University of Bari Aldo Moro, with a focus on
machine learning. During the Master's program, I completed numerous ML projects
related to computer vision and NLP, culminating in my thesis on automatic
artwork captioning. I also collaborated for four months with the National Research Council of Italy, where I extended
my BSc thesis work on text complexity assessment with machine learning.
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Research
I'm interested in computer vision, multimodal deep learning (particularly
vision and language), and generative models (MLLMs and diffusion models),
especially in the context of artwork analysis.
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Art2Mus: Bridging Visual Arts and Music through Cross-Modal Generation
Ivan Rinaldi, Nicola Fanelli, Giovanna Castellano, Gennaro Vessio
European Conference on Computer Vision (ECCV) Workshops, 2024
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We extend the AudioLDM2 architecture to generate music from artworks on a dataset of image-music pairings collected using ImageBind.
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Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Prompts
Pasquale De Marinis, Nicola Fanelli, Raffaele Scaringi, Emanuele Colonna, Giuseppe Fiameni, Gennaro Vessio, Giovanna Castellano
ArXiv, 2024
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We present Label Anything, an innovative neural network architecture designed for few-shot semantic segmentation (FSS). Label Anything supports multi-class segmentation with points, boxes, or masks as prompts and relaxes multiple constraints in support set creation for FSS.
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Converso: Improving LLM Chatbot Interfaces and Task Execution via Conversational Forms
Gianfranco Demarco, Nicola Fanelli, Gennaro Vessio, Giovanna Castellano
European Conference on Artificial Intelligence (ECAI) Workshops, 2024
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We develop a fully-containerized architecture for creating LLM chatbots and improve their performances in data acquisition with conversational forms.
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Exploring the Synergy Between Vision-Language Pretraining and ChatGPT for Artwork Captioning: A Preliminary Study
Giovanna Castellano, Nicola Fanelli, Raffaele Scaringi, Gennaro Vessio
International Conference on Image Analysis and Processing (ICIAP) Workshops, 2023
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We explore caption generation for digitized artworks using a noisy dataset of LLM-generated descriptions. We introduce CLIPScore
weighting to weigh the importance of each caption based on its quality to improve performances.
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