activity
20182021
most citedReal-Time Highly Accurate Dense Depth on a Power Budget using an FPGA-CPU Hybrid SoC

16 citations · 19 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2021

Plugging Self-Supervised Monocular Depth into Unsupervised Domain Adaptation for Semantic Segmentation

Adriano Cardace, Luca De Luigi, Pierluigi Zama Ramirez +2

Although recent semantic segmentation methods have made remarkable progress, they still rely on large amounts of annotated training data, which are often infeasible to collect in t…

cs.CV20201 cited

SAFFIRE: System for Autonomous Feature Filtering and Intelligent ROI Estimation

Marco Boschi, Luigi Di Stefano, Martino Alessandrini

This work introduces a new framework, named SAFFIRE, to automatically extract a dominant recurrent image pattern from a set of image samples. Such a pattern shall be used to elimin…

cs.CV20192 cited

Boosting Object Recognition in Point Clouds by Saliency Detection

Marlon Marcon, Riccardo Spezialetti, Samuele Salti +2

Object recognition in 3D point clouds is a challenging task, mainly when time is an important factor to deal with, such as in industrial applications. Local descriptors are an amen…

cs.CV2019

Learning an Effective Equivariant 3D Descriptor Without Supervision

Riccardo Spezialetti, Samuele Salti, Luigi Di Stefano

Establishing correspondences between 3D shapes is a fundamental task in 3D Computer Vision, typically addressed by matching local descriptors. Recently, a few attempts at applying…

cs.CV2019

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…

cs.CV201916 cited

Real-Time Highly Accurate Dense Depth on a Power Budget using an FPGA-CPU Hybrid SoC

Oscar Rahnama, Tommaso Cavallari, Stuart Golodetz +5

Obtaining highly accurate depth from stereo images in real time has many applications across computer vision and robotics, but in some contexts, upper bounds on power consumption c…