Publications (5)
(DE)^2 CO: Deep Depth Colorization
F. M. Carlucci, P. Russo, B. Caputo
The ability to classify objects is fundamental for robots. Besides knowledge about their visual appearance, captured by the RGB channel, robots heavily need also depth information…
D4D: An RGBD diffusion model to boost monocular depth estimation
L. Papa, P. Russo, I. Amerini
Ground-truth RGBD data are fundamental for a wide range of computer vision applications; however, those labeled samples are difficult to collect and time-consuming to produce. A co…
Developments in ROOT I/O and trees
R. Brun, P. Canal, M. Frank +4
For the last several months the main focus of development in the ROOT I/O package has been code consolidation and performance improvements. Access to remote files is affected both…
A Survey of Astronomical Research: An Astronomy for Development Baseline
V. A. R. M. Ribeiro, P. Russo, A. Cardenas-Avendano
Measuring scientific development is a difficult task. Different metrics have been put forward to evaluate scientific development; in this paper we explore a metric that uses the nu…
METER: a mobile vision transformer architecture for monocular depth estimation
L. Papa, P. Russo, I. Amerini
Depth estimation is a fundamental knowledge for autonomous systems that need to assess their own state and perceive the surrounding environment. Deep learning algorithms for depth…