260 citations · 321 across the 45 of their papers we have counts for
8 papers · 1 filter
Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail
Luca Bartolomei, Fabio Tosi, Matteo Poggi +1
We introduce Stereo Anywhere, a novel stereo-matching framework that combines geometric constraints with robust priors from monocular depth Vision Foundation Models (VFMs). By eleg…
Self-Evolving Depth-Supervised 3D Gaussian Splatting from Rendered Stereo Pairs
Sadra Safadoust, Fabio Tosi, Fatma Güney +1
3D Gaussian Splatting (GS) significantly struggles to accurately represent the underlying 3D scene geometry, resulting in inaccuracies and floating artifacts when rendering depth m…
Diffusion Models for Monocular Depth Estimation: Overcoming Challenging Conditions
Fabio Tosi, Pierluigi Zama Ramirez, Matteo Poggi
We present a novel approach designed to address the complexities posed by challenging, out-of-distribution data in the single-image depth estimation task. Starting with images that…
A Survey on Deep Stereo Matching in the Twenties
Fabio Tosi, Luca Bartolomei, Matteo Poggi
Stereo matching is close to hitting a half-century of history, yet witnessed a rapid evolution in the last decade thanks to deep learning. While previous surveys in the late 2010s…
Active Stereo in the Wild through Virtual Pattern Projection
Luca Bartolomei, Matteo Poggi, Fabio Tosi +2
This paper presents a novel general-purpose guided stereo paradigm that mimics the active stereo principle by replacing the unreliable physical pattern projector with a depth senso…
Federated Online Adaptation for Deep Stereo
Matteo Poggi, Fabio Tosi
We introduce a novel approach for adapting deep stereo networks in a collaborative manner. By building over principles of federated learning, we develop a distributed framework all…
The Third Monocular Depth Estimation Challenge
Jaime Spencer, Fabio Tosi, Matteo Poggi +38
This paper discusses the results of the third edition of the Monocular Depth Estimation Challenge (MDEC). The challenge focuses on zero-shot generalization to the challenging SYNS-…
How NeRFs and 3D Gaussian Splatting are Reshaping SLAM: a Survey
Fabio Tosi, Youmin Zhang, Ziren Gong +4
Over the past two decades, research in the field of Simultaneous Localization and Mapping (SLAM) has undergone a significant evolution, highlighting its critical role in enabling a…