6 papers
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…
RANa: Retrieval-Augmented Navigation
Gianluca Monaci, Rafael S. Rezende, Romain Deffayet +5
Methods for navigation based on large-scale learning typically treat each episode as a new problem, where the agent is spawned with a clean memory in an unknown environment. While…
PanSt3R: Multi-view Consistent Panoptic Segmentation
Lojze Zust, Yohann Cabon, Juliette Marrie +4
Panoptic segmentation of 3D scenes, involving the segmentation and classification of object instances in a dense 3D reconstruction of a scene, is a challenging problem, especially…
Test-time Vocabulary Adaptation for Language-driven Object Detection
Mingxuan Liu, Tyler L. Hayes, Massimiliano Mancini +3
Open-vocabulary object detection models allow users to freely specify a class vocabulary in natural language at test time, guiding the detection of desired objects. However, vocabu…
MUSt3R: Multi-view Network for Stereo 3D Reconstruction
Yohann Cabon, Lucas Stoffl, Leonid Antsfeld +4
DUSt3R introduced a novel paradigm in geometric computer vision by proposing a model that can provide dense and unconstrained Stereo 3D Reconstruction of arbitrary image collection…