169 citations · 461 across the 29 of their papers we have counts for
35 papers
Model-based Metric 3D Shape and Motion Reconstruction of Wild Bottlenose Dolphins in Drone-Shot Videos
Daniele Baieri, Riccardo Cicciarella, Michael Krützen +2
We address the problem of estimating the metric 3D shape and motion of wild dolphins from monocular video, with the aim of assessing their body condition. While considerable progre…
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…
ReMatching: Low-Resolution Representations for Scalable Shape Correspondence
Filippo Maggioli, Daniele Baieri, Emanuele Rodolà +1
We introduce \emph{ReMatching}, a novel shape correspondence solution based on the functional maps framework. Our method, by exploiting a new and appropriate \emph{re}-meshing para…
Fluid Dynamics Network: Topology-Agnostic 4D Reconstruction via Fluid Dynamics Priors
Daniele Baieri, Stefano Esposito, Filippo Maggioli +1
Representing 3D surfaces as level sets of continuous functions over is the common denominator of neural implicit representations, which recently enabled remarkable p…
Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching
Ramana Sundararaman, Riccardo Marin, Emanuele Rodola +1
In this work we present a novel approach for computing correspondences between non-rigid objects, by exploiting a reduced representation of deformation fields. Different from exist…