activity
20182022
most citedA CNN Based Approach for the Point-Light Photometric Stereo Problem

22 citations · 26 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV202222 cited

A CNN Based Approach for the Point-Light Photometric Stereo Problem

Fotios Logothetis, Roberto Mecca, Ignas Budvytis +1

Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagat…

cs.LG2021

Graph Convolutional Memory using Topological Priors

Steven D. Morad, Stephan Liwicki, Ryan Kortvelesy +2

Solving partially-observable Markov decision processes (POMDPs) is critical when applying reinforcement learning to real-world problems, where agents have an incomplete view of the…

cs.CV2021

LUCES: A Dataset for Near-Field Point Light Source Photometric Stereo

Roberto Mecca, Fotios Logothetis, Ignas Budvytis +1

Three-dimensional reconstruction of objects from shading information is a challenging task in computer vision. As most of the approaches facing the Photometric Stereo problem use s…

cs.CV20204 cited

A CNN Based Approach for the Near-Field Photometric Stereo Problem

Fotios Logothetis, Ignas Budvytis, Roberto Mecca +1

Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagat…

cs.RO2020

Embodied Visual Navigation with Automatic Curriculum Learning in Real Environments

Steven D. Morad, Roberto Mecca, Rudra P. K. Poudel +2

We present NavACL, a method of automatic curriculum learning tailored to the navigation task. NavACL is simple to train and efficiently selects relevant tasks using geometric featu…

cs.CV2018

A Differential Volumetric Approach to Multi-View Photometric Stereo

Fotios Logothetis, Roberto Mecca, Roberto Cipolla

Highly accurate 3D volumetric reconstruction is still an open research topic where the main difficulty is usually related to merging some rough estimations with high frequency deta…