Papers 3D Feature Matching
“3D Feature Matching” 태그가 달린 논문 19편 · 필터 해제
AxisPose: Model-Free Matching-Free Single-Shot 6D Object Pose Estimation via Axis Generation
Object pose estimation, which plays a vital role in robotics, augmented reality, and autonomous driving, has been of great interest in computer vision. Existing studies either require multi-stage pose regression or rely …
3D Feature Matching6D Pose Estimation6D Pose Estimation using RGBAutonomous Driving+3PointRecon: Online Point-based 3D Reconstruction via Ray-based 2D-3D Matching
We propose a novel online, point-based 3D reconstruction method from posed monocular RGB videos. Our model maintains a global point cloud representation of the scene, continuously updating the features and 3D locations o…
3D Feature Matching3D ReconstructionRigid Single-Slice-in-Volume registration via rotation-equivariant 2D/3D feature matching
2D to 3D registration is essential in tasks such as diagnosis, surgical navigation, environmental understanding, navigation in robotics, autonomous systems, or augmented reality. In medical imaging, the aim is often to p…
3D Feature MatchingEP2P-Loc: End-to-End 3D Point to 2D Pixel Localization for Large-Scale Visual Localization
Visual localization is the task of estimating a 6-DoF camera pose of a query image within a provided 3D reference map. Thanks to recent advances in various 3D sensors, 3D point clouds are becoming a more accurate and aff…
3D Feature MatchingImage to Point Cloud RegistrationKeypoint DetectionPoint Cloud Registration+2Efficient and Deterministic Search Strategy Based on Residual Projections for Point Cloud Registration with Correspondences
Estimating the rigid transformation between two LiDAR scans through putative 3D correspondences is a typical point cloud registration paradigm. Current 3D feature matching approaches commonly lead to numerous outlier cor…
3D Feature MatchingPoint Cloud RegistrationImproving Feature-based Visual Localization by Geometry-Aided Matching
Feature matching is crucial in visual localization, where 2D-3D correspondence plays a major role in determining the accuracy of camera pose. A sufficient number of well-distributed 2D-3D correspondences is essential for…
3D Feature MatchingPose EstimationVisual LocalizationPoints to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition
While the Transformer architecture has become ubiquitous in the machine learning field, its adaptation to 3D shape recognition is non-trivial. Due to its quadratic computational complexity, the self-attention operator qu…
3D Feature Matching3D Point Cloud Classification3D Shape RecognitionPoint Cloud RegistrationLepard: Learning partial point cloud matching in rigid and deformable scenes
We present Lepard, a Learning based approach for partial point cloud matching in rigid and deformable scenes. The key characteristics are the following techniques that exploit 3D positional knowledge for point cloud matc…
3D Feature Matching3D Point Cloud MatchingPartial Point Cloud MatchingPoint Cloud Registration+1Practical, Fast and Robust Point Cloud Registration for 3D Scene Stitching and Object Localization
3D point cloud registration ranks among the most fundamental problems in remote sensing, photogrammetry, robotics and geometric computer vision. Due to the limited accuracy of 3D feature matching techniques, outliers may…
3D Feature MatchingBenchmarkingObject LocalizationPoint Cloud RegistrationPRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features
Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown. In this paper, we propose a brand new point-set learning framework PRIN, namely, P…
3D Feature MatchingData AugmentationTowards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution
Visual information extraction (VIE) has attracted considerable attention recently owing to its various advanced applications such as document understanding, automatic marking and intelligent education. Most existing work…
3D Feature Matchingdocument understandingText DetectionText SpottingStickyPillars: Robust and Efficient Feature Matching on Point Clouds using Graph Neural Networks
Robust point cloud registration in real-time is an important prerequisite for many mapping and localization algorithms. Traditional methods like ICP tend to fail without good initialization, insufficient overlap or in th…
3D Feature MatchingPoint Cloud RegistrationHuman Correspondence Consensus for 3D Object Semantic Understanding
Semantic understanding of 3D objects is crucial in many applications such as object manipulation. However, it is hard to give a universal definition of point-level semantics that everyone would agree on. We observe that …
3D Feature Matching3D Point Cloud MatchingObjectFully Convolutional Geometric Features
Extracting geometric features from 3D scans or point clouds is the first step in applications such as registration, reconstruction, and tracking. State-of-the-art methods require computing low-level features as input or …
3D Feature Matching3D Point Cloud Matching3D Shape RepresentationMetric Learning+1Multi-scale Cross-form Pyramid Network for Stereo Matching
Stereo matching plays an indispensable part in autonomous driving, robotics and 3D scene reconstruction. We propose a novel deep learning architecture, which called CFP-Net, a Cross-Form Pyramid stereo matching network f…
3D Feature Matching3D Scene ReconstructionAutonomous DrivingForm+23D Point Capsule Networks
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule networks arise as a direct consequence o…
3D Feature Matching3D Geometry Perception3D Object Classification3D Object Reconstruction+6Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution
Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown. In this paper, we propose a brand new point-set learning framework PRIN, namely, P…
3D Feature MatchingData AugmentationEfficient Global 2D-3D Matching for Camera Localization in a Large-Scale 3D Map
Given an image of a street scene in a city, this paper develops a new method that can quickly and precisely pinpoint at which location (as well as viewing direction) the image was taken, against a pre-stored large-scale …
3D Feature MatchingCamera LocalizationFast Rotation Search with Stereographic Projections for 3D Registration
Recently there has been a surge of interest to use branch-and-bound (bnb) optimisation for 3D point cloud registration. While bnb guarantees globally optimal solutions, it is usually too slow to be practical. A fundament…
3D Feature MatchingGeometric MatchingPoint Cloud RegistrationTranslation