6 citations · 8 across the 4 of their papers we have counts for
6 papers
Leveraging commonsense for object localisation in partial scenes
Francesco Giuliari, Geri Skenderi, Marco Cristani +2
We propose an end-to-end solution to address the problem of object localisation in partial scenes, where we aim to estimate the position of an object in an unknown area given only…
Under the Hood of Transformer Networks for Trajectory Forecasting
Luca Franco, Leonardo Placidi, Francesco Giuliari +3
Transformer Networks have established themselves as the de-facto state-of-the-art for trajectory forecasting but there is currently no systematic study on their capability to model…
Spatial Commonsense Graph for Object Localisation in Partial Scenes
Francesco Giuliari, Geri Skenderi, Marco Cristani +2
We solve object localisation in partial scenes, a new problem of estimating the unknown position of an object (e.g. where is the bag?) given a partial 3D scan of a scene. The propo…
POMP++: Pomcp-based Active Visual Search in unknown indoor environments
Francesco Giuliari, Alberto Castellini, Riccardo Berra +5
In this paper we focus on the problem of learning online an optimal policy for Active Visual Search (AVS) of objects in unknown indoor environments. We propose POMP++, a planning s…
POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments
Yiming Wang, Francesco Giuliari, Riccardo Berra +5
In this paper we focus on the problem of learning an optimal policy for Active Visual Search (AVS) of objects in known indoor environments with an online setup. Our POMP method use…
Transformer Networks for Trajectory Forecasting
Francesco Giuliari, Irtiza Hasan, Marco Cristani +1
Most recent successes on forecasting the people motion are based on LSTM models and all most recent progress has been achieved by modelling the social interaction among people and…