356 citations · 819 across the 28 of their papers we have counts for
32 papers · 1 filter
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…
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…
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…
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…
What could go wrong? Discovering and describing failure modes in computer vision
Gabriela Csurka, Tyler L. Hayes, Diane Larlus +1
Deep learning models are effective, yet brittle. Even carefully trained, their behavior tends to be hard to predict when confronted with out-of-distribution samples. In this work,…
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…
SHiNe: Semantic Hierarchy Nexus for Open-vocabulary Object Detection
Mingxuan Liu, Tyler L. Hayes, Elisa Ricci +2
Open-vocabulary object detection (OvOD) has transformed detection into a language-guided task, empowering users to freely define their class vocabularies of interest during inferen…
Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency
Yannis Kalantidis, Mert Bülent Sarıyıldız, Rafael S. Rezende +3
State-of-the-art visual localization approaches generally rely on a first image retrieval step whose role is crucial. Yet, retrieval often struggles when facing varying conditions,…
RaSP: Relation-aware Semantic Prior for Weakly Supervised Incremental Segmentation
Subhankar Roy, Riccardo Volpi, Gabriela Csurka +1
Class-incremental semantic image segmentation assumes multiple model updates, each enriching the model to segment new categories. This is typically carried out by providing expensi…
Semantic Image Segmentation: Two Decades of Research
Gabriela Csurka, Riccardo Volpi, Boris Chidlovskii
Semantic image segmentation (SiS) plays a fundamental role in a broad variety of computer vision applications, providing key information for the global understanding of an image. T…
CroCo v2: Improved Cross-view Completion Pre-training for Stereo Matching and Optical Flow
Philippe Weinzaepfel, Thomas Lucas, Vincent Leroy +7
Despite impressive performance for high-level downstream tasks, self-supervised pre-training methods have not yet fully delivered on dense geometric vision tasks such as stereo mat…
CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion
Philippe Weinzaepfel, Vincent Leroy, Thomas Lucas +7
Masked Image Modeling (MIM) has recently been established as a potent pre-training paradigm. A pretext task is constructed by masking patches in an input image, and this masked con…
Investigating the Role of Image Retrieval for Visual Localization -- An exhaustive benchmark
Martin Humenberger, Yohann Cabon, Noé Pion +5
Visual localization, i.e., camera pose estimation in a known scene, is a core component of technologies such as autonomous driving and augmented reality. State-of-the-art localizat…
Deep Visual Geo-localization Benchmark
Gabriele Berton, Riccardo Mereu, Gabriele Trivigno +4
In this paper, we propose a new open-source benchmarking framework for Visual Geo-localization (VG) that allows to build, train, and test a wide range of commonly used architecture…
On the Road to Online Adaptation for Semantic Image Segmentation
Riccardo Volpi, Pau de Jorge, Diane Larlus +1
We propose a new problem formulation and a corresponding evaluation framework to advance research on unsupervised domain adaptation for semantic image segmentation. The overall goa…
ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity
Ginger Delmas, Rafael Sampaio de Rezende, Gabriela Csurka +1
An intuitive way to search for images is to use queries composed of an example image and a complementary text. While the first provides rich and implicit context for the search, th…
Unsupervised Domain Adaptation for Semantic Image Segmentation: a Comprehensive Survey
Gabriela Csurka, Riccardo Volpi, Boris Chidlovskii
Semantic segmentation plays a fundamental role in a broad variety of computer vision applications, providing key information for the global understanding of an image. Yet, the stat…
Domain Adaptation in Multi-View Embedding for Cross-Modal Video Retrieval
Jonathan Munro, Michael Wray, Diane Larlus +2
Given a gallery of uncaptioned video sequences, this paper considers the task of retrieving videos based on their relevance to an unseen text query. To compensate for the lack of a…
Large-scale Localization Datasets in Crowded Indoor Spaces
Donghwan Lee, Soohyun Ryu, Suyong Yeon +8
Estimating the precise location of a camera using visual localization enables interesting applications such as augmented reality or robot navigation. This is particularly useful in…
Deep Visual Domain Adaptation
Gabriela Csurka
Domain adaptation (DA) aims at improving the performance of a model on target domains by transferring the knowledge contained in different but related source domains. With recent a…
Benchmarking Image Retrieval for Visual Localization
Noé Pion, Martin Humenberger, Gabriela Csurka +2
Visual localization, i.e., camera pose estimation in a known scene, is a core component of technologies such as autonomous driving and augmented reality. State-of-the-art localizat…
Robust Image Retrieval-based Visual Localization using Kapture
Martin Humenberger, Yohann Cabon, Nicolas Guerin +7
Visual localization tackles the challenge of estimating the camera pose from images by using correspondence analysis between query images and a map. This task is computation and da…