Mikhail Giorgini — accepted AI-conference papers

2023

Self-Supervised Category-Level 6D Object Pose Estimation With Optical Flow Consistency

Michela Zaccaria, Fabian Manhardt, Yan Di, Federico Tombari, Jacopo Aleotti, Mikhail Giorgini

RA-L 2023

Category-level 6D object pose estimation aims at determining the pose of an object of a given category. Most current state-of-the-art methods require a significant amount of real training data to supervise their models. Moreover, annotating the 6D pose is very time consuming, error-prone, and it doe

Cited by 19 Source ↗Scholar ↗

2017

Ground Segmentation From Large-Scale Terrestrial Laser Scanner Data of Industrial Environments

Mikhail Giorgini, Federico Barbieri, Jacopo Aleotti

RA-L 2017

In many 3-D perception applications, ground segmentation is a necessary preprocessing phase together with point cloud cleaning and outlier removal. This letter presents a method for ground segmentation in large-scale point clouds of industrial environments acquired using a terrestrial laser scanner

Cited by 7 Source ↗Scholar ↗