3 citations · 4 across the 11 of their papers we have counts for
11 papers
Collaborative Visual Place Recognition through Federated Learning
Mattia Dutto, Gabriele Berton, Debora Caldarola +3
Visual Place Recognition (VPR) aims to estimate the location of an image by treating it as a retrieval problem. VPR uses a database of geo-tagged images and leverages deep neural n…
The Unreasonable Effectiveness of Pre-Trained Features for Camera Pose Refinement
Gabriele Trivigno, Carlo Masone, Barbara Caputo +1
Pose refinement is an interesting and practically relevant research direction. Pose refinement can be used to (1) obtain a more accurate pose estimate from an initial prior (e.g.,…
Segmentation Re-thinking Uncertainty Estimation Metrics for Semantic Segmentation
Qitian Ma, Shyam Nanda Rai, Carlo Masone +1
In the domain of computer vision, semantic segmentation emerges as a fundamental application within machine learning, wherein individual pixels of an image are classified into dist…
JIST: Joint Image and Sequence Training for Sequential Visual Place Recognition
Gabriele Berton, Gabriele Trivigno, Barbara Caputo +1
Visual Place Recognition aims at recognizing previously visited places by relying on visual clues, and it is used in robotics applications for SLAM and localization. Since typicall…
EarthLoc: Astronaut Photography Localization by Indexing Earth from Space
Gabriele Berton, Alex Stoken, Barbara Caputo +1
Astronaut photography, spanning six decades of human spaceflight, presents a unique Earth observations dataset with immense value for both scientific research and disaster response…
The Robust Semantic Segmentation UNCV2023 Challenge Results
Xuanlong Yu, Yi Zuo, Zitao Wang +34
This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023. The challenge was centered around semantic segment…