activity
20222024
most citedGO-SLAM: Global Optimization for Consistent 3D Instant Reconstruction

3 citations · 11 across the 16 of their papers we have counts for

collaborators

16 papers

cs.CV2024

LiDAR-Event Stereo Fusion with Hallucinations

Luca Bartolomei, Matteo Poggi, Andrea Conti +1

Event stereo matching is an emerging technique to estimate depth from neuromorphic cameras; however, events are unlikely to trigger in the absence of motion or the presence of larg…

cs.CV2024

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…

cs.CV2024

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-…

cs.CV2024

Range-Agnostic Multi-View Depth Estimation With Keyframe Selection

Andrea Conti, Matteo Poggi, Valerio Cambareri +1

Methods for 3D reconstruction from posed frames require prior knowledge about the scene metric range, usually to recover matching cues along the epipolar lines and narrow the searc…

cs.CV20232 cited

GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor Scenes

Chaoqiang Zhao, Matteo Poggi, Fabio Tosi +4

This paper tackles the challenges of self-supervised monocular depth estimation in indoor scenes caused by large rotation between frames and low texture. We ease the learning proce…

cs.CV2023

Active Stereo Without Pattern Projector

Luca Bartolomei, Matteo Poggi, Fabio Tosi +2

This paper proposes a novel framework integrating the principles of active stereo in standard passive camera systems without a physical pattern projector. We virtually project a pa…