3 citations · 3 across the 3 of their papers we have counts for
8 papers · 1 filter
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…
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…
What does CLIP know about peeling a banana?
Claudia Cuttano, Gabriele Rosi, Gabriele Trivigno +1
Humans show an innate capability to identify tools to support specific actions. The association between objects parts and the actions they facilitate is usually named affordance. B…
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.,…
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…
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…