10 citations · 10 across the 16 of their papers we have counts for
16 papers
SUFLECA: Scaling Up Feature Learning for CAD-to-image Alignment
Saad Ejaz, Miguel Fernandez-Cortizas, Javier Civera +2
CAD-to-image alignment aims to estimate an object's 9D pose (rotation, translation, and anisotropic scale) from a single RGB image, with applications in robotics and augmented real…
SSMB: Self-Supervised Local Feature Detection under Motion Blur
Zhenjun Zhao, Fabio Bellavia, Wenting Wang +6
Keypoint detection under motion blur remains a significant challenge, as blur distorts local image structure and degrades the repeatability of feature localization. Existing approa…
Visual Relocalization from Sparse Views in Aliased and Low-Texture Environments via Novel View Synthesis
Maria Peribañez, Javier Civera, Rudolph Triebel +1
Visual localization becomes extremely challenging in planetary-like terrains characterized by low texture, perceptual aliasing, harsh illumination, and sparse, weakly overlapping v…
Non-Minimal Sampling and Consensus for Prohibitively Large Datasets
Seong Hun Lee, Patrick Vandewalle, Javier Civera
We introduce NONSAC (Non-Minimal Sampling and Consensus), a general framework for robust and scalable model estimation from arbitrarily large datasets contaminated with noise and o…
PAGaS: Pixel-Aligned 1DoF Gaussian Splatting for Depth Refinement
David Recasens, Robert Maier, Aljaz Bozic +4
Gaussian Splatting (GS) has emerged as an efficient approach for high-quality novel view synthesis. While early GS variants struggled to accurately model the scene's geometry, rece…
P3P Made Easy
Seong Hun Lee, Patrick Vandewalle, Javier Civera
We revisit the classical Perspective-Three-Point (P3P) problem, which aims to recover the absolute pose of a calibrated camera from three 2D-3D correspondences. It has long been kn…
MVSAnywhere: Zero-Shot Multi-View Stereo
Sergio Izquierdo, Mohamed Sayed, Michael Firman +6
Computing accurate depth from multiple views is a fundamental and longstanding challenge in computer vision. However, most existing approaches do not generalize well across differe…
Single-Shot Metric Depth from Focused Plenoptic Cameras
Blanca Lasheras-Hernandez, Klaus H. Strobl, Sergio Izquierdo +3
Metric depth estimation from visual sensors is crucial for robots to perceive, navigate, and interact with their environment. Traditional range imaging setups, such as stereo or st…
Alignment Scores: Robust Metrics for Multiview Pose Accuracy Evaluation
Seong Hun Lee, Javier Civera
We propose three novel metrics for evaluating the accuracy of a set of estimated camera poses given the ground truth: Translation Alignment Score (TAS), Rotation Alignment Score (R…
Tightly Coupled SLAM with Imprecise Architectural Plans
Muhammad Shaheer, Jose Andres Millan-Romera, Hriday Bavle +4
Robots navigating indoor environments often have access to architectural plans, which can serve as prior knowledge to enhance their localization and mapping capabilities. While som…
Close, But Not There: Boosting Geographic Distance Sensitivity in Visual Place Recognition
Sergio Izquierdo, Javier Civera
Visual Place Recognition (VPR) plays a critical role in many localization and mapping pipelines. It consists of retrieving the closest sample to a query image, in a certain embeddi…
Camera Motion Estimation from RGB-D-Inertial Scene Flow
Samuel Cerezo, Javier Civera
In this paper, we introduce a novel formulation for camera motion estimation that integrates RGB-D images and inertial data through scene flow. Our goal is to accurately estimate t…
Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture Environments
Alberto García-Hernández, Riccardo Giubilato, Klaus H. Strobl +2
Perceptual aliasing and weak textures pose significant challenges to the task of place recognition, hindering the performance of Simultaneous Localization and Mapping (SLAM) system…
PCR-99: A Practical Method for Point Cloud Registration with 99 Percent Outliers
Seong Hun Lee, Javier Civera, Patrick Vandewalle
We propose a robust method for point cloud registration that can handle both unknown scales and extreme outlier ratios. Our method, dubbed PCR-99, uses a deterministic 3-point samp…
From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation
Javier Tirado-Garín, Javier Civera
Estimating the relative camera pose from correspondences between two calibrated views is a fundamental task in computer vision. This process typically involves two stage…
Optimal Transport Aggregation for Visual Place Recognition
Sergio Izquierdo, Javier Civera
The task of Visual Place Recognition (VPR) aims to match a query image against references from an extensive database of images from different places, relying solely on visual cues.…