Giulia Rizzoli | Ph.D. Student

Phone (office): +39 049 827 7774

Biography

Giulia Rizzoli is a PhD student in Information Engineering at the Department of Information Engineering of the University of Padua.
She received her Bachelor’s degree in Information Engineering in 2019 and her Master’s Degree with honors in ICT for Internet and Multimedia in 2021, both from the University of Padova.
As part of her master’s thesis, she conducted research at Sony in Stuttgart, Germany.
Her research interests include multi-modal learning, domain adaptation, federated and continual learning applied to computer vision tasks.

Research areas

Multi-Modal Learning

Multimodal learning is an area of machine learning that deals with integrating and analysing information from multiple modalities, such as text, images, audio, and video.

Federated Learning

Federated learning is a decentralized machine learning approach that allows multiple devices to train a shared model collaboratively while keeping their local data private.

Domain Adaptation

Domain Adaptation aligns a network from a source dataset to perform on a target dataset with a different distribution. Complex neural networks require abundant labeled data, which limits their application in many real-world scenarios.

Continual Learning


Continual learning refers to the ability of a machine learning model to continuously acquire and retain knowledge from new data while retaining previously learned information. 

Publications

2024

Rizzoli, Giulia; Shenaj, Donald; Zanuttigh, Pietro

Source-Free Domain Adaptation for RGB-D Semantic Segmentation with Vision Transformers Proceedings Article

In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 615–624, 2024.

Links | BibTeX

2023

Barbato, Francesco; Rizzoli, Giulia; Zanuttigh, Pietro

DepthFormer: Multimodal Positional Encodings and Cross-Input Attention for Transformer-Based Segmentation Networks Proceedings Article

In: ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.

BibTeX

Rizzoli, Giulia; Barbato, Francesco; Caligiuri, Matteo; Zanuttigh, Pietro

SynDrone-Multi-Modal UAV Dataset for Urban Scenarios Proceedings Article

In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 2210–2220, 2023.

BibTeX

Shenaj, Donald; Rizzoli, Giulia; Zanuttigh, Pietro

Federated Learning in Computer Vision Journal Article

In: IEEE Access, 2023.

BibTeX

Liu, Chang; Rizzoli, Giulia; Barbato, Francesco; Michieli, Umberto; Niu, Yi; Zanuttigh, Pietro

RECALL+: Adversarial Web-based Replay for Continual Learning in Semantic Segmentation Journal Article

In: arXiv preprint arXiv:2309.10479, 2023.

BibTeX

2022

Rizzoli, Giulia; Barbato, Francesco; Zanuttigh, Pietro

Multimodal Semantic Segmentation in Autonomous Driving: A Review of Current Approaches and Future Perspectives Journal Article

In: Technologies, vol. 10, no. 4, pp. 90, 2022.

Links | BibTeX

Jung, HyunJun; Wu, Shun-Cheng; Ruhkamp, Patrick; Schieber, Hannah; Wang, Pengyuan; Rizzoli, Giulia; Zhao, Hongcheng; Meier, Sven Damian; Roth, Daniel; Navab, Nassir; others,

HouseCat6D–A Large-Scale Multi-Modal Category Level 6D Object Pose Dataset with Household Objects in Realistic Scenarios Journal Article

In: arXiv preprint arXiv:2212.10428, 2022.

BibTeX