5 citations · 8 across the 7 of their papers we have counts for
4 papers · 1 filter
SShaDe: scalable shape deformation via local representations
Filippo Maggioli, Daniele Baieri, Zorah Lähner +1
With the increase in computational power for the available hardware, the demand for high-resolution data in computer graphics applications increases. Consequently, classical geomet…
: Cycle-Consistent Multi-Model Merging
Donato Crisostomi, Marco Fumero, Daniele Baieri +2
In this paper, we present a novel data-free method for merging neural networks in weight space. Differently from most existing works, our method optimizes for the permutations of n…
Implicit-ARAP: Efficient Handle-Guided Neural Field Deformation via Local Patch Meshing
Daniele Baieri, Filippo Maggioli, Emanuele Rodolà +2
Neural fields have emerged as a powerful representation for 3D geometry, enabling compact and continuous modeling of complex shapes. Despite their expressive power, manipulating ne…
GSEdit: Efficient Text-Guided Editing of 3D Objects via Gaussian Splatting
Francesco Palandra, Andrea Sanchietti, Daniele Baieri +1
We present GSEdit, a pipeline for text-guided 3D object editing based on Gaussian Splatting models. Our method enables the editing of the style and appearance of 3D objects without…