4 citations · 10 across the 9 of their papers we have counts for
10 papers
A temporal graph dissimilarity measure capturing epidemic spreading behavior
Salvatore Freni, Lorenzo Dall'Amico, Francesca Pistilli +3
Comparing temporal networks is a challenging problem in network analysis. Commonly adopted methods compare structural properties of temporal graphs and can be highly sensitive to t…
Learning reusable concepts across different egocentric video understanding tasks
Simone Alberto Peirone, Francesca Pistilli, Antonio Alliegro +2
Our comprehension of video streams depicting human activities is naturally multifaceted: in just a few moments, we can grasp what is happening, identify the relevance and interacti…
FORESCENE: FOREcasting human activity via latent SCENE graphs diffusion
Antonio Alliegro, Francesca Pistilli, Tatiana Tommasi +1
Forecasting human-environment interactions in daily activities is challenging due to the high variability of human behavior. While predicting directly from videos is possible, it i…
MaskPlanner: Learning-Based Object-Centric Motion Generation from 3D Point Clouds
Gabriele Tiboni, Raffaello Camoriano, Tatiana Tommasi
Object-Centric Motion Generation (OCMG) plays a key role in a variety of industrial applications$\unicode{x2014}$such as robotic spray painting and welding$\unicode{x2014}$requirin…
Hier-EgoPack: Hierarchical Egocentric Video Understanding with Diverse Task Perspectives
Simone Alberto Peirone, Francesca Pistilli, Antonio Alliegro +2
Our comprehension of video streams depicting human activities is naturally multifaceted: in just a few moments, we can grasp what is happening, identify the relevance and interacti…
Segmentation Re-thinking Uncertainty Estimation Metrics for Semantic Segmentation
Qitian Ma, Shyam Nanda Rai, Carlo Masone +1
In the domain of computer vision, semantic segmentation emerges as a fundamental application within machine learning, wherein individual pixels of an image are classified into dist…
PolyDiff: Generating 3D Polygonal Meshes with Diffusion Models
Antonio Alliegro, Yawar Siddiqui, Tatiana Tommasi +1
We introduce PolyDiff, the first diffusion-based approach capable of directly generating realistic and diverse 3D polygonal meshes. In contrast to methods that use alternate 3D sha…
MeshGPT: Generating Triangle Meshes with Decoder-Only Transformers
Yawar Siddiqui, Antonio Alliegro, Alexey Artemov +5
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 b…
Domain Randomization via Entropy Maximization
Gabriele Tiboni, Pascal Klink, Jan Peters +3
Varying dynamics parameters in simulation is a popular Domain Randomization (DR) approach for overcoming the reality gap in Reinforcement Learning (RL). Nevertheless, DR heavily hi…
OpenPatch: a 3D patchwork for Out-Of-Distribution detection
Paolo Rabino, Antonio Alliegro, Francesco Cappio Borlino +1
Moving deep learning models from the laboratory setting to the open world entails preparing them to handle unforeseen conditions. In several applications the occurrence of novel cl…