Recent advances in machine learning have led to increased interest in solving visual
computing problems using methods that employ coordinate‐based neural networks. These …

We propose a novel framework for finding correspondences in images based on a deep
neural network that, given two images and a query point in one of them, finds its …

We present a novel method for reconstructing a 3D implicit surface from a large-scale,
sparse, and noisy point cloud. Our approach builds upon the recently introduced Neural …

Tracking non-rigidly deforming scenes using range sensors has numerous applications
including computer vision, AR/VR, and robotics. However, due to occlusions and physical …

Abstract We present Neural Kernel Fields: a novel method for reconstructing implicit 3D
shapes based on a learned kernel ridge regression. Our technique achieves state-of-the-art …

In this paper, we propose a transformer-based procedure for the efficient registration of non-
rigid 3D point clouds. The proposed approach is data-driven and adopts for the first time the …

This paper presents Fauno, the first and largest open-source Italian conversational Large
Language Model (LLM). Our goal with Fauno is to democratize the study of LLMs in Italian …

The emergence of large language models (LLMs) has revolutionized machine learning and
related fields, showcasing remarkable abilities in comprehending, generating, and …

In deformable object manipulation, we often want to interact with specific segments of an
object that are only defined in non-deformed models of the object. We thus require a system …

Teeth scans are essential for many applications in orthodontics, where the teeth structures
are virtualized to facilitate the design and fabrication of the prosthetic piece. Nevertheless …