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Tobia Poppi
I'm a PhD candidate in the National PhD in Artificial Intelligence at the University of Pisa, conducting my research at AImageLab, the research laboratory of the Department of Engineering "Enzo Ferrari" at the University of Modena and Reggio Emilia. My specialization areas include |
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Research
My research focuses on advancing Passionate about leveraging AI to solve complex societal challenges, I am dedicated to ensuring AI systems are safe, transparent, and aligned with responsible principles, driving innovation with a human-centric approach. |
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Hyperbolic Safety-Aware Vision-Language Models
Tobia Poppi, Tejaswi Kasarla, Pascal Mettes, Lorenzo Baraldi, Rita Cucchiara IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025 project page / arXiv / code / model HySAC, Hyperbolic Safety-Aware CLIP, models hierarchical safety relations to enable effective retrieval of unsafe content, dynamically redirecting it to safer alternatives for enhanced content moderation. |
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Safe-CLIP: Removing NSFW Concepts from Vision-and-Language Models
Samuele Poppi, Tobia Poppi, Federico Cocchi, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara European Conference on Computer Vision, 2024 project page / bibtex / arXiv / code / models Vision-and-language model designed to mitigate the risks associated with NSFW content in AI applications. Safe-CLIP is fine-tuned to serve the association between linguistic and visual concepts, ensuring safer outputs in text-to-image and image-to-text retrieval and generation tasks. |
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Towards Trustworthy AI: LLM Aligning for Offensive Content Removal
Tobia Poppi, Samuele Poppi, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara 2023 morethesis A study on aligning Large Language Models (LLMs) for offensive content removal, introducing the CAiA dataset and Safe-CLIP to ensure ethical and responsible AI-driven content moderation. |
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Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation
Elena Govi, Davide Sapienza, Carmelo Scribano, Tobia Poppi, Giorgia Franchini, Paola Ardòn, Micaela Verucchi, Marko Bertogna 2023 arXiv An investigation into background-induced bias in 6-DoF object pose estimation, revealing how ArUco markers in datasets like Linemod influence model predictions and proposing mitigation strategies using dataset augmentation and saliency map analysis. |
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Deep Learning for DeepFake Detection
Tobia Poppi, Elena Govi, Fabio Marinelli 2022 A deep learning pipeline for DeepFake detection, leveraging custom datasets and an optimized Xception-based CNN to identify manipulated facial images with high accuracy." |
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Il labelling: i migliori tool disponibili e la loro applicazione per il rilevamento di persone e cartelli stradali e per la pose estimation di oggetti 3D
Tobia Poppi 2021 arXiv A comprehensive study of data labeling tools and techniques, evaluating their efficiency in person and traffic sign detection, as well as 3D pose estimation for robotic applications. |
Participation to National and European Projects |
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ELIAS - European Lighthouse of AI for Sustainability
ELIAS aims at establishing Europe as a leader in Artificial Intelligence (AI) research that drives sustainable innovation and economic development. |
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FAIR - Future Artificial Intelligence Research
The FAIR project is a national scale, multidisciplinary initiative aimed at reimagining and developing large-scale foundational models. It explores research questions, methodologies, models, technologies, as well as ethical and legal frameworks for creating Artificial Intelligence systems capable of interacting and collaborating with humans. |
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ELSA - European Lighthouse on Secure and Safe AI
ELSA is a virtual center of excellence that will spearhead efforts in foundational safe and secure artificial intelligence (AI) methodology research. |
Selected Activities as Reviewer |
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Website created by Tobia | HTML template forked from Jon Barron |