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
HouseCat6D-A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios Proceedings Article
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 22498–22508, 2024, (Highlight).
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.
Learning from the Web: Language Drives Weakly-Supervised Incremental Learning for Semantic Segmentation Proceedings Article
In: European Conference on Computer Vision, Springer 2024.
2023
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.
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.
Federated Learning in Computer Vision Journal Article
In: IEEE Access, 2023.
RECALL+: Adversarial Web-based Replay for Continual Learning in Semantic Segmentation Journal Article
In: arXiv preprint arXiv:2309.10479, 2023.
2022
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.