4 papers
R3ST: A Synthetic 3D Dataset With Realistic Trajectories
Simone Teglia, Claudia Melis Tonti, Francesco Pro +4
Datasets are essential to train and evaluate computer vision models used for traffic analysis and to enhance road safety. Existing real datasets fit real-world scenarios, capturing…
Enhancing Ground-to-Aerial Image Matching for Visual Misinformation Detection Using Semantic Segmentation
Emanuele Mule, Matteo Pannacci, Ali Ghasemi Goudarzi +4
The recent advancements in generative AI techniques, which have significantly increased the online dissemination of altered images and videos, have raised serious concerns about th…
A Semantic Segmentation-guided Approach for Ground-to-Aerial Image Matching
Francesco Pro, Nikolaos Dionelis, Luca Maiano +2
Nowadays the accurate geo-localization of ground-view images has an important role across domains as diverse as journalism, forensics analysis, transports, and Earth Observation. T…
Learning from Unlabelled Data with Transformers: Domain Adaptation for Semantic Segmentation of High Resolution Aerial Images
Nikolaos Dionelis, Francesco Pro, Luca Maiano +2
Data from satellites or aerial vehicles are most of the times unlabelled. Annotating such data accurately is difficult, requires expertise, and is costly in terms of time. Even if…