no code implementations • 22 Apr 2025 • Daniele Baieri, Riccardo Cicciarella, Michael Krützen, Emanuele Rodolà, Silvia Zuffi
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.
1 code implementation • 28 May 2024 • Donato Crisostomi, Marco Fumero, Daniele Baieri, Florian Bernard, Emanuele Rodolà
In this paper, we present a novel data-free method for merging neural networks in weight space.
no code implementations • 21 May 2024 • Daniele Baieri, Filippo Maggioli, Zorah Lähner, Simone Melzi, Emanuele Rodolà
Then, we apply this representation in the setting of handle-guided deformation: we introduce two distinct pipelines, which make use of 3D neural fields to compute As-Rigid-As-Possible deformations of both high-resolution meshes and neural fields under a given set of constraints.
no code implementations • 8 Mar 2024 • Francesco Palandra, Andrea Sanchietti, Daniele Baieri, Emanuele Rodolà
We present GSEdit, a pipeline for text-guided 3D object editing based on Gaussian Splatting models.
no code implementations • 17 Mar 2023 • Daniele Baieri, Stefano Esposito, Filippo Maggioli, Emanuele Rodolà
Representing 3D surfaces as level sets of continuous functions over $\mathbb{R}^3$ is the common denominator of neural implicit representations, which recently enabled remarkable progress in geometric deep learning and computer vision tasks.
no code implementations • 22 Jun 2022 • Stefano Esposito, Daniele Baieri, Stefan Zellmann, André Hinkenjann, Emanuele Rodolà
NeRF-based techniques fit wide and deep multi-layer perceptrons (MLPs) to a continuous radiance field that can be rendered from any unseen viewpoint.