AI for Good
AIGO utilizes state-of-the-art multimodal models, with a special attention to vision, and Foundation Models to interpret complex signals from various modalities, including video, audio, and language. The team aims at developing efficient and scalable AI solutions for high-impact sectors such as healthcare, assisted living, and industrial applications.
5
Active Projects
25
Team Members
14
Publications
Our Team
Relevant Papers
2026
Shiri M., Beyan C., Murino V.
MADPOT: Medical Anomaly Detection with CLIP Adaptation and Partial Optimal Transport
Lecture Notes in Computer Science, vol. 16167 LNCS, pp. 247-259
2025
Serez D., Cristani M., Del Bue A., Murino V., Morerio P.
A Mutual Information Perspective on Multiple Latent Variable Generative Models for Positive View Generation
Transactions on Machine Learning Research, vol. 2025-September
2025
Ciranni M., Pastore V.P., Di Via R., Tartaglione E., Odone F., Murino V.
Diffusing DeBias: Synthetic Bias Amplification for Model Debiasing
Neural Information Processing Systems
2025
Zanin G., Biswas R., Morerio P., Barbon S., Carini A., Del Bue A., Murino V.
Direction-Aware Room Impulse Response Estimation for Immersive Audio Rendering in Real Environments
MM 2025 - Proceedings of the 33rd ACM International Conference on Multimedia, Co-Located with MM 2025, pp. 8116-8124
2025
Fitzgibbon A., Leal-Taixe L., Murino V., Russakovsky O.
Foreword
Lecture Notes in Computer Science, vol. 15064 LNCS, pp. v-vi
2025
Yang M.Y., Rota P., Mancini M., Morerio P., Rosenhahn B., Murino V.
Guest Editorial: Special Issue on Multimodal Learning
International Journal of Computer Vision, vol. 133, (no. 5), pp. 3079-3081