@inproceedings{scarpellini2024diffassemble,author={Giuliari, Francesco and Scarpellini, Gianluca and Fiorini, Stefano and Morerio, Pietro and {Del Bue}, Alessio},title={DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D Reassembly},booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},month=jun,year={2024},}
2023
ArXiv
Positional Diffusion: Ordering Unordered Sets with Diffusion Probabilistic Models
Francesco Giuliari, Gianluca Scarpellini , Stuart James , and 2 more authors
@inproceedings{giuliari2023positional,title={Positional Diffusion: Ordering Unordered Sets with Diffusion Probabilistic Models},author={Giuliari, Francesco and Scarpellini, Gianluca and James, Stuart and Wang, Yiming and Bue, Alessio Del},year={2023},eprint={2303.11120},booktitle={ArXiv},primaryclass={cs.CV}}
Pattern Recognition
Under the hood of transformer networks for trajectory forecasting
Luca Franco , Leonardo Placidi , Francesco Giuliari, and 3 more authors
Transformer Networks have established themselves as the de-facto state-of-the-art for trajectory forecasting but there is currently no systematic study on their capability to model the motion patterns of people, without interactions with other individuals nor the social context. There is abundant literature on LSTMs, CNNs and GANs on this subject. However methods adopting Transformer techniques achieve great performances by complex models and a clear analysis of their adoption as plain sequence models is missing. This paper proposes the first in-depth study of Transformer Networks (TF) and the Bidirectional Transformers (BERT) for the forecasting of the individual motion of people, without bells and whistles. We conduct an exhaustive evaluation of the input/output representations, problem formulations and sequence modelling, including a novel analysis of their capability to predict multi-modal futures. Out of comparative evaluation on the ETH+UCY benchmark, both TF and BERT are top performers in predicting individual motions and remain within a narrow margin wrt more complex techniques, including both social interactions and scene contexts. Source code will be released for all conducted experiments.
@article{FRANCO2023109372,title={Under the hood of transformer networks for trajectory forecasting},journal={Pattern Recognition},volume={138},pages={109372},year={2023},issn={0031-3203},doi={https://doi.org/10.1016/j.patcog.2023.109372},url={https://www.sciencedirect.com/science/article/pii/S0031320323000730},author={Franco, Luca and Placidi, Leonardo and Giuliari, Francesco and Hasan, Irtiza and Cristani, Marco and Galasso, Fabio},keywords={Trajectory forecasting, Human behavior, Transformer networks, BERT, Multi-modal future prediction},}
2022
CVPR
Spatial Commonsense Graph for Object localisation in Partial Scenes
Francesco Giuliari, Geri Skenderi , Marco Cristani , and 2 more authors
@inproceedings{giuliari2021pomp++,title={POMP++: Pomcp-based Active Visual Search in unknown indoor environments},author={Giuliari, Francesco and Castellini, Alberto and Berra, Riccardo and Del Bue, Alessio and Farinelli, Alessandro and Cristani, Marco and Setti, Francesco and Wang, Yiming},booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},pages={1523--1530},organization={IEEE},year={2021},}
2020
BMVC
POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments
Yiming Wang , Francesco Giuliari, Riccardo Berra , and 5 more authors
@inproceedings{wang2020pomp,title={POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments},author={Wang, Yiming and Giuliari, Francesco and Berra, Riccardo and Castellini, Alberto and Del Bue, Alessio and Farinelli, Alessandro and Cristani, Marco and Setti, Francesco},booktitle={BMVC},year={2020},}
ICPR
Transformer networks for trajectory forecasting
Francesco Giuliari, Irtiza Hasan , Marco Cristani , and 1 more author
In 2020 25th International Conference on Pattern Recognition (ICPR) , Jun 2020
@inproceedings{giuliari2021transformer,title={Transformer networks for trajectory forecasting},author={Giuliari, Francesco and Hasan, Irtiza and Cristani, Marco and Galasso, Fabio},booktitle={2020 25th International Conference on Pattern Recognition (ICPR)},pages={10335--10342},year={2020},organization={IEEE},}
2018
BMVC
Understanding Deep Architectures by Visual Summaries
Marco Godi , Marco Carletti , Maya Aghaei , and 2 more authors
@inproceedings{Godi2018UnderstandingDA,title={Understanding Deep Architectures by Visual Summaries},author={Godi, Marco and Carletti, Marco and Aghaei, Maya and Giuliari, Francesco and Cristani, Marco},booktitle={BMVC},year={2018},}