Winner of the Essay Competition at International Computer Vision Summer School (ICVSS) 2025 Permalink
I was the winner of the essay competition, with the essay titled Transparency Is All You Need: The Social Dilemma of Generative AI
I was the winner of the essay competition, with the essay titled Transparency Is All You Need: The Social Dilemma of Generative AI
I was the Local Arrangement Chair of the Verimedia workshop.
The workshop addresses the rising challenges of AI-generated content and deepfakes by exploring advancements in multimedia forensics, deepfake detection, adversarial machine learning, AI-generated media attribution, multimodal analysis. A key focus is lifelong media authentication, emphasizing AI’s role in safeguarding media integrity by analyzing diverse media types—text, images, videos, and speech. The session highlights the critical importance of combating disinformation and ensuring trustworthy information across fields like forensics, fake news debunking, cyberattack mitigation, and politics. The primary objective is to bring together experts from these varied fields, policy makers and stakeholders to share challenges and solutions and foster collaborative discussions.
Important Info:
📊 Modelling and querying of a countries-states-cities dataset with SQL (Postgresql) and NOSQL (Neo4j) approaches. Optimization of SQL and NOSQL queries to reduce the execution time.
⌨️ Reimplementation of Top Linux shell command.
🕹 Implementation of DQfD tested on Pong Gym environment and Montezuma Revenge Gym environment (the latter with sparse reward).
🖥 This web app allows the rapid inizialitazion of projects on GitLab through a very simple user interface. By filling in the required fields, the project will be created directly on your GitLab account.
🔭 Web app allowing students to write reviews on some exams in order to help other students in preparing for those exams.
🛡️ Official repository of the paper Explainability Driven Adversarial Robustness Assessment for Generalized Deepfake-Detectors. We propose a framework to perform explainaility-driven adversarial attacks on generalized deepfake detectors and to evaluate their security and robustness under different attack scenarios.
📈 Implementation of the famous Geometric Algebra Transformer to deal with geometric data. A modification of its attention module has been performed to study the equivariance of the architecture.
🖥 This project aims to deform the shape of an input mesh by following a set of 2D guidance images representing the desired output mesh. We use Pytorch3D and exploit a neural network to predict the shape deformation.
🦿 A reactive architecture made up of three controllers allows Tiago Robot to grasp and place a static object on-the-move (i.e. without stopping). The results are more gracefulness in the entire task execution and a minor task execution time.
📚 Implementation of homeworks for the Hot Topics in NLP course of the Master degree in Artificial Intelligence & Robotics at Sapienza University of Rome.
🦾 This project consists of a ROS support for a Multi-robot simulator written in C++.
🦾 Implementation of Lagrangian Neural Network tested on one-single link rigid robot and one-single link elastic robot.
🔋 Official repository of the paper Optimize Vision Transformers Architecture via Efficient Attention Modules: A Study on the Monocular Depth Estimation Task. Two modifications of METER attention module are proposed and implemented to build two more efficient versions: Meta-METER and Pyra-METER.
🧲 This project presents the architecture and application of the Uformer neural network.
Published in International Conference on Image Analysis and Processing, 2023
Recommended citation: Schiavella, C., Cirillo, L., Papa, L., Russo, P., & Amerini, I. (2023, September). Optimize Vision Transformer Architecture via Efficient Attention Modules: A Study on the Monocular Depth Estimation Task. In International Conference on Image Analysis and Processing (pp. 383-394). Cham: Springer Nature Switzerland.
Published in Scientific Reports Journal volume 15, 2025
Recommended citation: Schiavella, C., Cirillo, L., Papa, L. et al. Efficient attention vision transformers for monocular depth estimation on resource-limited hardware. Sci Rep 15, 24001 (2025). https://doi.org/10.1038/s41598-025-06112-8
Published in EURASIP Journal on Information Security 2025, 2025
Recommended citation: Cirillo, L., Gervasio, A. & Amerini, I. Explainability-driven adversarial robustness assessment for generalized deepfake detectors. EURASIP J. on Info. Security 2025, 23 (2025). https://doi.org/10.1186/s13635-025-00211-9
I was the winner of the essay competition, with the essay titled Transparency Is All You Need: The Social Dilemma of Generative AI
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Master in Artificial Intelligence & Robotics, Sapienza University of Rome, Department of Computer, Automatic and Management Engineering (DIAG), 2025
Teacher Assistant of the Computer Vision course held by Prof. Irene Amerini.
I taught lessons for the Master students:
For any information about the practical lessons and related Google Colab notebooks, contact me at cirillo@diag.uniroma1.it