3 citations · 3 across the 3 of their papers we have counts for
5 papers
ReLight My NeRF: A Dataset for Novel View Synthesis and Relighting of Real World Objects
Marco Toschi, Riccardo De Matteo, Riccardo Spezialetti +3
In this paper, we focus on the problem of rendering novel views from a Neural Radiance Field (NeRF) under unobserved light conditions. To this end, we introduce a novel dataset, du…
NeRF-Supervised Deep Stereo
Fabio Tosi, Alessio Tonioni, Daniele De Gregorio +1
We introduce a novel framework for training deep stereo networks effortlessly and without any ground-truth. By leveraging state-of-the-art neural rendering solutions, we generate s…
ScanNeRF: a Scalable Benchmark for Neural Radiance Fields
Luca De Luigi, Damiano Bolognini, Federico Domeniconi +3
In this paper, we propose the first-ever real benchmark thought for evaluating Neural Radiance Fields (NeRFs) and, in general, Neural Rendering (NR) frameworks. We design and imple…
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…
SkiMap: An Efficient Mapping Framework for Robot Navigation
Daniele De Gregorio, Luigi Di Stefano
We present a novel mapping framework for robot navigation which features a multi-level querying system capable to obtain rapidly representations as diverse as a 3D voxel grid, a 2.…