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Found 12 papers, 6 papers with code
An Accurate and Real-time Relative Pose Estimation from Triple Point-line Images by Decoupling Rotation and Translation
First, a high-precision rotation estimation method based on normal vector coplanarity constraints that consider the uncertainty of observations is proposed, which can be solved by Levenberg-Marquardt (LM) algorithm efficiently.
Geometric Wide-Angle Camera Calibration: A Review and Comparative Study
These tests reveal the strengths and weaknesses of these camera models, as well as the repeatability of these GCC tools.
A Rotation-Translation-Decoupled Solution for Robust and Efficient Visual-Inertial Initialization
We propose a novel visual-inertial odometry (VIO) initialization method, which decouples rotation and translation estimation, and achieves higher efficiency and better robustness.
MVSTER: Epipolar Transformer for Efficient Multi-View Stereo
Therefore, we present MVSTER, which leverages the proposed epipolar Transformer to learn both 2D semantics and 3D spatial associations efficiently.
ELSD: Efficient Line Segment Detector and Descriptor
The line description ability of ELSD also outperforms the previous works on the line matching task.
Ranked #1 on
Line Segment Detection
on wireframe dataset
Improved Signed Distance Function for 2D Real-time SLAM and Accurate Localization
In this paper, we propose an improved Signed Distance Function (SDF) for both 2D SLAM and pure localization to improve the accuracy of mapping and localization.
PL-VINS: Real-Time Monocular Visual-Inertial SLAM with Point and Line Features
This paper presents PL-VINS, a real-time optimization-based monocular VINS method with point and line features, developed based on the state-of-the-art point-based VINS-Mono \cite{vins}.
TP-LSD: Tri-Points Based Line Segment Detector
To realize one-step detection with a faster and more compact model, we introduce the tri-points representation, converting the line segment detection to the end-to-end prediction of a root-point and two endpoints for each line segment.
Ranked #2 on
Line Segment Detection
on York Urban Dataset
M^3VSNet: Unsupervised Multi-metric Multi-view Stereo Network
To improve the robustness and completeness of point cloud reconstruction, we propose a novel multi-metric loss function that combines pixel-wise and feature-wise loss function to learn the inherent constraints from different perspectives of matching correspondences.
M^3VSNet: Unsupervised Multi-metric Multi-view Stereo Network
To improve the robustness and completeness of point cloud reconstruction, we propose a novel multi-metric loss function that combines pixel-wise and feature-wise loss function to learn the inherent constraints from different perspectives of matching correspondences.
Leveraging Planar Regularities for Point Line Visual-Inertial Odometry
To improve the accuracy of 3D mesh generation and localization, we propose a tightly-coupled monocular VIO system, PLP-VIO, which exploits point features and line features as well as plane regularities.
Coarse-To-Fine Visual Localization Using Semantic Compact Map
Robust visual localization for urban vehicles remains challenging and unsolved.
