5 papers
Privacy-Preserving Structureless Visual Localization via Image Obfuscation
Vojtech Panek, Patrik Beliansky, Zuzana Kukelova +1
Visual localization is the task of estimating the camera pose of an image relative to a scene representation. In practice, visual localization systems are often cloud-based. Natura…
Can we make NeRF-based visual localization privacy-preserving?
Maxime Pietrantoni, Martin Humenberger, Torsten Sattler +1
Visual localization (VL) is the task of estimating the camera pose in a known scene. VL methods, a.o., can be distinguished based on how they represent the scene, e.g., explicitly…
Gaussian Splatting Feature Fields for Privacy-Preserving Visual Localization
Maxime Pietrantoni, Gabriela Csurka, Torsten Sattler
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 pr…
Self-supervised Learning of Neural Implicit Feature Fields for Camera Pose Refinement
Maxime Pietrantoni, Gabriela Csurka, Martin Humenberger +1
Visual localization techniques rely upon some underlying scene representation to localize against. These representations can be explicit such as 3D SFM map or implicit, such as a n…
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.,…