Maxime Pietrantoni — accepted AI-conference papers

2025

Gaussian Splatting Feature Fields for (Privacy-Preserving) Visual Localization

Maxime Pietrantoni, Gabriela Csurka, Torsten Sattler

CVPR 2025poster

Visual localization is the task of estimating a camera pose in a known environment. In this paper, we utilize 3D Gaussian Splatting (3DGS)-based representations for accurate and privacy-preserving visual localization. We propose Gaussian Splatting Feature Fields (GSFFs), a scene representation for v…

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2023

SegLoc: Learning Segmentation-Based Representations for Privacy-Preserving Visual Localization

Maxime Pietrantoni, Martin Humenberger, Torsten Sattler, Gabriela Csurka

CVPR 2023poster

Inspired by properties of semantic segmentation, in this paper we investigate how to leverage robust image segmentation in the context of privacy-preserving visual localization. We propose a new localization framework, SegLoc, that leverages image segmentation to create robust, compact, and privacy-…

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