10 citations · 17 across the 13 of their papers we have counts for
13 papers
Cross-Modal and Uncertainty-Aware Agglomeration for Open-Vocabulary 3D Scene Understanding
Jinlong Li, Cristiano Saltori, Fabio Poiesi +1
The lack of a large-scale 3D-text corpus has led recent works to distill open-vocabulary knowledge from vision-language models (VLMs). However, these methods typically rely on a si…
Novel class discovery meets foundation models for 3D semantic segmentation
Luigi Riz, Cristiano Saltori, Yiming Wang +2
The task of Novel Class Discovery (NCD) in semantic segmentation entails training a model able to accurately segment unlabelled (novel) classes, relying on the available supervisio…
Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation
Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni +3
Deep-learning models for 3D point cloud semantic segmentation exhibit limited generalization capabilities when trained and tested on data captured with different sensors or in vary…
Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation
Cristiano Saltori, Aljoša Ošep, Elisa Ricci +1
The ability to deploy robots that can operate safely in diverse environments is crucial for developing embodied intelligent agents. As a community, we have made tremendous progress…
Novel Class Discovery for 3D Point Cloud Semantic Segmentation
Luigi Riz, Cristiano Saltori, Elisa Ricci +1
Novel class discovery (NCD) for semantic segmentation is the task of learning a model that can segment unlabelled (novel) classes using only the supervision from labelled (base) cl…
Overlap-guided Gaussian Mixture Models for Point Cloud Registration
Guofeng Mei, Fabio Poiesi, Cristiano Saltori +3
Probabilistic 3D point cloud registration methods have shown competitive performance in overcoming noise, outliers, and density variations. However, registering point cloud pairs i…
Wave equation for Sturm-Liouville operator with singular intermediate coefficient and potential
Michael Ruzhansky, Alibek Yeskermessuly
In this paper, we consider a wave equation on a bounded domain with a Sturm-Liouville operator with a singular intermediate coefficient and a singular potential. To obtain and eval…
CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation
Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni +3
3D LiDAR semantic segmentation is fundamental for autonomous driving. Several Unsupervised Domain Adaptation (UDA) methods for point cloud data have been recently proposed to impro…
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation
Cristiano Saltori, Evgeny Krivosheev, Stéphane Lathuilière +5
3D point cloud semantic segmentation is fundamental for autonomous driving. Most approaches in the literature neglect an important aspect, i.e., how to deal with domain shift when…
SF-UDA: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object Detection
Cristiano Saltori, Stéphane Lathuiliére, Nicu Sebe +2
3D object detectors based only on LiDAR point clouds hold the state-of-the-art on modern street-view benchmarks. However, LiDAR-based detectors poorly generalize across domains due…
Low-Budget Label Query through Domain Alignment Enforcement
Jurandy Almeida, Cristiano Saltori, Paolo Rota +1
Deep learning revolution happened thanks to the availability of a massive amount of labelled data which have contributed to the development of models with extraordinary inference c…
Incremental learning for the detection and classification of GAN-generated images
Francesco Marra, Cristiano Saltori, Giulia Boato +1
Current developments in computer vision and deep learning allow to automatically generate hyper-realistic images, hardly distinguishable from real ones. In particular, human face g…
Regularized Evolutionary Algorithm for Dynamic Neural Topology Search
Cristiano Saltori, Subhankar Roy, Nicu Sebe +1
Designing neural networks for object recognition requires considerable architecture engineering. As a remedy, neuro-evolutionary network architecture search, which automatically se…