22 citations · 41 across the 22 of their papers we have counts for
24 papers
FoundYou: A Unified Model for Personalized Segmentation and Retrieval
Gabriele Trivigno, Marcos Alfaro, Claudia Cuttano +3
Personalized segmentation and personalized retrieval both aim to identify the same physical object across different images. While the former localizes the object within a target im…
A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens
Tommie Kerssies, Gabriele Berton, Ju He +5
Anticipating diverse future states is a central challenge in video world modeling. Discriminative world models produce a deterministic prediction that implicitly averages over poss…
Are Pretrained Image Matchers Good Enough for SAR-Optical Satellite Registration?
Isaac Corley, Alex Stoken, Gabriele Berton
Cross-modal optical--SAR (Synthetic Aperture Radar) registration is a bottleneck in remote-sensing disaster response. Modern image matchers are developed and benchmarked almost exc…
AsymLoc: Towards Asymmetric Feature Matching for Efficient Visual Localization
Mohammad Omama, Gabriele Berton, Eric Foxlin +1
Precise and real-time visual localization is critical for applications like AR/VR and robotics, especially on resource-constrained edge devices such as smart glasses, where battery…
CompLLM: Compression for Long Context Q&A
Gabriele Berton, Jayakrishnan Unnikrishnan, Son Tran +1
Large Language Models (LLMs) face significant computational challenges when processing long contexts due to the quadratic complexity of self-attention. While soft context compressi…
To Match or Not to Match: Revisiting Image Matching for Reliable Visual Place Recognition
Davide Sferrazza, Gabriele Berton, Gabriele Trivigno +1
Visual Place Recognition (VPR) is a critical task in computer vision, traditionally enhanced by re-ranking retrieval results with image matching. However, recent advancements in VP…
All You Need to Know About Training Image Retrieval Models
Gabriele Berton, Kevin Musgrave, Carlo Masone
Image retrieval is the task of finding images in a database that are most similar to a given query image. The performance of an image retrieval pipeline depends on many training-ti…
MegaLoc: One Retrieval to Place Them All
Gabriele Berton, Carlo Masone
Retrieving images from the same location as a given query is an important component of multiple computer vision tasks, like Visual Place Recognition, Landmark Retrieval, Visual Loc…
AstroLoc: Robust Space to Ground Image Localizer
Gabriele Berton, Alex Stoken, Carlo Masone
Astronauts take thousands of photos of Earth per day from the International Space Station, which, once localized on Earth's surface, are used for a multitude of tasks, ranging from…
MeshVPR: Citywide Visual Place Recognition Using 3D Meshes
Gabriele Berton, Lorenz Junglas, Riccardo Zaccone +3
Mesh-based scene representation offers a promising direction for simplifying large-scale hierarchical visual localization pipelines, combining a visual place recognition step based…
Scale-Free Image Keypoints Using Differentiable Persistent Homology
Giovanni Barbarani, Francesco Vaccarino, Gabriele Trivigno +3
In computer vision, keypoint detection is a fundamental task, with applications spanning from robotics to image retrieval; however, existing learning-based methods suffer from scal…
EarthMatch: Iterative Coregistration for Fine-grained Localization of Astronaut Photography
Gabriele Berton, Gabriele Goletto, Gabriele Trivigno +3
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 d…
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…
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…
EigenPlaces: Training Viewpoint Robust Models for Visual Place Recognition
Gabriele Berton, Gabriele Trivigno, Barbara Caputo +1
Visual Place Recognition is a task that aims to predict the place of an image (called query) based solely on its visual features. This is typically done through image retrieval, wh…
Divide&Classify: Fine-Grained Classification for City-Wide Visual Place Recognition
Gabriele Trivigno, Gabriele Berton, Juan Aragon +2
Visual Place recognition is commonly addressed as an image retrieval problem. However, retrieval methods are impractical to scale to large datasets, densely sampled from city-wide…
Are Local Features All You Need for Cross-Domain Visual Place Recognition?
Giovanni Barbarani, Mohamad Mostafa, Hajali Bayramov +4
Visual Place Recognition is a task that aims to predict the coordinates of an image (called query) based solely on visual clues. Most commonly, a retrieval approach is adopted, whe…
Learning Sequential Descriptors for Sequence-based Visual Place Recognition
Riccardo Mereu, Gabriele Trivigno, Gabriele Berton +2
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 pl…
Rethinking Visual Geo-localization for Large-Scale Applications
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. To investigate…
Deep Visual Geo-localization Benchmark
Gabriele Berton, Riccardo Mereu, Gabriele Trivigno +4
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 architecture…
Learning Semantics for Visual Place Recognition through Multi-Scale Attention
Valerio Paolicelli, Antonio Tavera, Carlo Masone +2
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 galle…
Viewpoint Invariant Dense Matching for Visual Geolocalization
Gabriele Berton, Carlo Masone, Valerio Paolicelli +1
In this paper we propose a novel method for image matching based on dense local features and tailored for visual geolocalization. Dense local features matching is robust against ch…
Adaptive-Attentive Geolocalization from few queries: a hybrid approach
Gabriele Moreno Berton, Valerio Paolicelli, Carlo Masone +1
We address the task of cross-domain visual place recognition, where the goal is to geolocalize a given query image against a labeled gallery, in the case where the query and the ga…