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20222026
most citedMeshVPR: Citywide Visual Place Recognition Using 3D Meshes

1 citations · 1 across the 9 of their papers we have counts for

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cs.CV2024

Egocentric zone-aware action recognition across environments

Simone Alberto Peirone, Gabriele Goletto, Mirco Planamente +3

Human activities exhibit a strong correlation between actions and the places where these are performed, such as washing something at a sink. More specifically, in daily living envi…

cs.CV2024★ 1 cited

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…

cs.CV2024

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…

cs.CV2024

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.,…

cs.CV2024

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…

cs.CV2024

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…