2 citations · 2 across the 3 of their papers we have counts for
3 papers
GRASPLAT: Enabling dexterous grasping through novel view synthesis
Matteo Bortolon, Nuno Ferreira Duarte, Plinio Moreno +3
Achieving dexterous robotic grasping with multi-fingered hands remains a significant challenge. While existing methods rely on complete 3D scans to predict grasp poses, these appro…
Multi-view data capture for dynamic object reconstruction using handheld augmented reality mobiles
M. Bortolon, L. Bazzanella, F. Poiesi
We propose a system to capture nearly-synchronous frame streams from multiple and moving handheld mobiles that is suitable for dynamic object 3D reconstruction. Each mobile execute…
Multi-view data capture using edge-synchronised mobiles
Matteo Bortolon, Paul Chippendale, Stefano Messelodi +1
Multi-view data capture permits free-viewpoint video (FVV) content creation. To this end, several users must capture video streams, calibrated in both time and pose, framing the sa…