no code implementations • 4 Jun 2024 • Gabriele Berton, Lorenz Junglas, Riccardo Zaccone, Thomas Pollok, Barbara Caputo, Carlo Masone
Mesh-based scene representation offers a promising direction for simplifying large-scale hierarchical visual localization pipelines, combining a visual place recognition step based on global features (retrieval) and a visual localization step based on local features.
1 code implementation • 3 Jun 2024 • Giovanni Barbarani, Francesco Vaccarino, Gabriele Trivigno, Marco Guerra, Gabriele Berton, Carlo Masone
In computer vision, keypoint detection is a fundamental task, with applications spanning from robotics to image retrieval; however, existing learning-based methods suffer from scale dependency and lack flexibility.
1 code implementation • 8 May 2024 • Gabriele Berton, Gabriele Goletto, Gabriele Trivigno, Alex Stoken, Barbara Caputo, Carlo Masone
Precise, pixel-wise geolocalization of astronaut photography is critical to unlocking the potential of this unique type of remotely sensed Earth data, particularly for its use in disaster management and climate change research.
no code implementations • 20 Apr 2024 • Mattia Dutto, Gabriele Berton, Debora Caldarola, Eros Fanì, Gabriele Trivigno, Carlo Masone
Visual Place Recognition (VPR) aims to estimate the location of an image by treating it as a retrieval problem.
1 code implementation • 28 Mar 2024 • Gabriele Berton, Gabriele Trivigno, Barbara Caputo, Carlo Masone
As a mitigation to this problem, we propose a novel Joint Image and Sequence Training protocol (JIST) that leverages large uncurated sets of images through a multi-task learning framework.
1 code implementation • CVPR 2024 • Gabriele Berton, Alex Stoken, Barbara Caputo, Carlo Masone
Astronaut photography, spanning six decades of human spaceflight, presents a unique Earth observations dataset with immense value for both scientific research and disaster response.
4 code implementations • ICCV 2023 • Gabriele Berton, Gabriele Trivigno, Barbara Caputo, Carlo Masone
Visual Place Recognition is a task that aims to predict the place of an image (called query) based solely on its visual features.
1 code implementation • 17 Jul 2023 • Gabriele Trivigno, Gabriele Berton, Juan Aragon, Barbara Caputo, Carlo Masone
Our method, Divide&Classify (D&C), enjoys the fast inference of classification solutions and an accuracy competitive with retrieval methods on the fine-grained, city-wide setting.
1 code implementation • 12 Apr 2023 • Giovanni Barbarani, Mohamad Mostafa, Hajali Bayramov, Gabriele Trivigno, Gabriele Berton, Carlo Masone, Barbara Caputo
Despite recent advances, recognizing the same place when the query comes from a significantly different distribution is still a major hurdle for state of the art retrieval methods.
1 code implementation • ICCV 2023 • Gabriele Trivigno, Gabriele Berton, Juan Aragon, Barbara Caputo, Carlo Masone
In this paper we investigate whether we can effectively approach this task as a classification problem, thus bypassing the need for a similarity search.
1 code implementation • 8 Jul 2022 • Riccardo Mereu, Gabriele Trivigno, Gabriele Berton, Carlo Masone, Barbara Caputo
In robotics, Visual Place Recognition is a continuous process that receives as input a video stream to produce a hypothesis of the robot's current position within a map of known places.
1 code implementation • CVPR 2022 • Gabriele Berton, Riccardo Mereu, Gabriele Trivigno, Carlo Masone, Gabriela Csurka, Torsten Sattler, Barbara Caputo
In this paper, we propose a new open-source benchmarking framework for Visual Geo-localization (VG) that allows to build, train, and test a wide range of commonly used architectures, with the flexibility to change individual components of a geo-localization pipeline.
2 code implementations • CVPR 2022 • Gabriele Berton, Carlo Masone, Barbara Caputo
Visual Geo-localization (VG) is the task of estimating the position where a given photo was taken by comparing it with a large database of images of known locations.
Ranked #2 on Visual Place Recognition on Nardo-Air R
1 code implementation • 24 Jan 2022 • Valerio Paolicelli, Antonio Tavera, Carlo Masone, Gabriele Berton, Barbara Caputo
In this paper we address the task of visual place recognition (VPR), where the goal is to retrieve the correct GPS coordinates of a given query image against a huge geotagged gallery.
1 code implementation • ICCV 2021 • Gabriele Berton, Carlo Masone, Valerio Paolicelli, Barbara Caputo
Dense local features matching is robust against changes in illumination and occlusions, but not against viewpoint shifts which are a fundamental aspect of geolocalization.