Dottorando in Ingegneria Informatica E Dei Sistemi , 37o ciclo (2021-2024)
Dipartimento di Automatica e Informatica (DAUIN)
Profilo
Dottorato di ricerca
Tutori
Didattica
Insegnamenti
Corso di laurea magistrale
- Machine learning and Deep learning. A.A. 2023/24, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
- Machine learning and Deep learning. A.A. 2022/23, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
Pubblicazioni
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- Cuttano, Claudia; Rosi, Gabriele; Trivigno, Gabriele; Averta, Giuseppe (2024)
What does CLIP know about peeling a banana?. In: Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle WA (USA), 16-22 June 2024, pp. 2238-2247. ISBN: 979-8-3503-6547-4
Contributo in Atti di Convegno (Proceeding) - Trivigno, Gabriele; Masone, Carlo; Caputo, Barbara; Sattler, Torsten (2024)
The Unreasonable Effectiveness of Pre-Trained Features for Camera Pose Refinement. In: IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), Seattle (USA), 16-22 June 2024, pp. 12786-12798. ISSN 2163-6648. ISBN: 979-8-3503-5300-6
Contributo in Atti di Convegno (Proceeding) - Berton, Gabriele; Goletto, Gabriele; Trivigno, Gabriele; Stoken, Alex; Caputo, Barbara; ... (2024)
EarthMatch: Iterative Coregistration for Fine-grained Localization of Astronaut Photography. In: IEEE / CVF Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle (USA), 17-18 June 2024, pp. 4264-4274. ISSN 2160-7508. ISBN: 979-8-3503-6547-4
Contributo in Atti di Convegno (Proceeding) - Barbarani, Giovanni; Vaccarino, Francesco; Trivigno, Gabriele; Guerra, Marco; Berton, ... (2024)
Scale-Free Image Keypoints Using Differentiable Persistent Homology. In: 41st International Conference on Machine Learning, Vienna (AUT), 21-27 July 2024, pp. 2990-3002. ISSN 2640-3498
Contributo in Atti di Convegno (Proceeding) - Dutto, Mattia; Berton, Gabriele; Caldarola, Debora; Fani, Eros; Trivigno, Gabriele; ... (2024)
Collaborative Visual Place Recognition through Federated Learning. In: IEEE / CVF Computer Vision and Pattern Recognition Conference Workshop, Seattle (USA), 17-18 June 2024, pp. 4215-4225. ISBN: 979-8-3503-6547-4
Contributo in Atti di Convegno (Proceeding)