16 citations · 16 across the 5 of their papers we have counts for
14 papers
TouchSDF: A DeepSDF Approach for 3D Shape Reconstruction using Vision-Based Tactile Sensing
Mauro Comi, Yijiong Lin, Alex Church +3
Humans rely on their visual and tactile senses to develop a comprehensive 3D understanding of their physical environment. Recently, there has been a growing interest in exploring a…
ParGAN: Learning Real Parametrizable Transformations
Diego Martin Arroyo, Alessio Tonioni, Federico Tombari
Current methods for image-to-image translation produce compelling results, however, the applied transformation is difficult to control, since existing mechanisms are often limited…
A Divide et Impera Approach for 3D Shape Reconstruction from Multiple Views
Riccardo Spezialetti, David Joseph Tan, Alessio Tonioni +2
Estimating the 3D shape of an object from a single or multiple images has gained popularity thanks to the recent breakthroughs powered by deep learning. Most approaches regress the…
Batch Normalization Embeddings for Deep Domain Generalization
Mattia Segu, Alessio Tonioni, Federico Tombari
Domain generalization aims at training machine learning models to perform robustly across different and unseen domains. Several recent methods use multiple datasets to train models…
Unsupervised Domain Adaptation for Depth Prediction from Images
Alessio Tonioni, Matteo Poggi, Stefano Mattoccia +1
State-of-the-art approaches to infer dense depth measurements from images rely on CNNs trained end-to-end on a vast amount of data. However, these approaches suffer a drastic drop…
Semi-Automatic Labeling for Deep Learning in Robotics
Daniele De Gregorio, Alessio Tonioni, Gianluca Palli +1
In this paper, we propose Augmented Reality Semi-automatic labeling (ARS), a semi-automatic method which leverages on moving a 2D camera by means of a robot, proving precise camera…