Search Results for author: Cristiano Saltori

Found 4 papers, 1 papers with code

SF-UDA$^{3D}$: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object Detection

1 code implementation16 Oct 2020 Cristiano Saltori, Stéphane Lathuiliére, Nicu Sebe, Elisa Ricci, Fabio Galasso

In the case of LiDAR, in fact, domain shift is not only due to changes in the environment and in the object appearances, as for visual data from RGB cameras, but is also related to the geometry of the point clouds (e. g., point density variations).

3D Object Detection Unsupervised Domain Adaptation

Low-Budget Label Query through Domain Alignment Enforcement

no code implementations1 Jan 2020 Jurandy Almeida, Cristiano Saltori, Paolo Rota, Nicu Sebe

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 capabilities.

Unsupervised Domain Adaptation

Incremental learning for the detection and classification of GAN-generated images

no code implementations3 Oct 2019 Francesco Marra, Cristiano Saltori, Giulia Boato, Luisa Verdoliva

Current developments in computer vision and deep learning allow to automatically generate hyper-realistic images, hardly distinguishable from real ones.

Classification Face Generation +2

Regularized Evolutionary Algorithm for Dynamic Neural Topology Search

no code implementations15 May 2019 Cristiano Saltori, Subhankar Roy, Nicu Sebe, Giovanni Iacca

Although very effective, evolutionary algorithms rely heavily on having a large population of individuals (i. e., network architectures) and is therefore memory expensive.

Neural Architecture Search Object Recognition

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