no code implementations • 5 Mar 2024 • Simone Alberto Peirone, Francesca Pistilli, Antonio Alliegro, Giuseppe Averta
Human comprehension of a video stream is naturally broad: in a few instants, we are able to understand what is happening, the relevance and relationship of objects, and forecast what will follow in the near future, everything all at once.
no code implementations • 18 Dec 2023 • Antonio Alliegro, Yawar Siddiqui, Tatiana Tommasi, Matthias Nießner
In contrast to methods that use alternate 3D shape representations (e. g. implicit representations), our approach is a discrete denoising diffusion probabilistic model that operates natively on the polygonal mesh data structure.
2 code implementations • 27 Nov 2023 • Yawar Siddiqui, Antonio Alliegro, Alexey Artemov, Tatiana Tommasi, Daniele Sirigatti, Vladislav Rosov, Angela Dai, Matthias Nießner
We introduce MeshGPT, a new approach for generating triangle meshes that reflects the compactness typical of artist-created meshes, in contrast to dense triangle meshes extracted by iso-surfacing methods from neural fields.
no code implementations • 5 Oct 2023 • Paolo Rabino, Antonio Alliegro, Francesco Cappio Borlino, Tatiana Tommasi
We advance the field by introducing OpenPatch that builds on a large pre-trained model and simply extracts from its intermediate features a set of patch representations that describe each known class.
1 code implementation • 23 Jul 2022 • Antonio Alliegro, Francesco Cappio Borlino, Tatiana Tommasi
In recent years there has been significant progress in the field of 3D learning on classification, detection and segmentation problems.
1 code implementation • CVPR 2021 • Antonio Alliegro, Diego Valsesia, Giulia Fracastoro, Enrico Magli, Tatiana Tommasi
The combined embedding inherits category-agnostic properties from the chosen pretext tasks.
no code implementations • 15 Apr 2020 • Antonio Alliegro, Davide Boscaini, Tatiana Tommasi
Point cloud processing and 3D shape understanding are very challenging tasks for which deep learning techniques have demonstrated great potentials.