A review of non-rigid transformations and learning-based 3D point cloud registration methods
Point cloud registration is a research field where the spatial relationship between two or
more sets of points in space is determined. Point clouds are found in multiple applications …
more sets of points in space is determined. Point clouds are found in multiple applications …
Coarse to fine-based image–point cloud fusion network for 3D object detection
Enhancing original LiDAR point cloud features with virtual points has gained widespread
attention in multimodal information fusion. However, existing methods struggle to leverage …
attention in multimodal information fusion. However, existing methods struggle to leverage …
Differentiable registration of images and lidar point clouds with voxelpoint-to-pixel matching
Cross-modality registration between 2D images captured by cameras and 3D point clouds
from LiDARs is a crucial task in computer vision and robotic. Previous methods estimate 2D …
from LiDARs is a crucial task in computer vision and robotic. Previous methods estimate 2D …
DeepI2P: Image-to-point cloud registration via deep classification
This paper presents DeepI2P: a novel approach for cross-modality registration between an
image and a point cloud. Given an image (eg from a rgb-camera) and a general point cloud …
image and a point cloud. Given an image (eg from a rgb-camera) and a general point cloud …
Deep learning for visual localization and map**: A survey
Deep-learning-based localization and map** approaches have recently emerged as a
new research direction and receive significant attention from both industry and academia …
new research direction and receive significant attention from both industry and academia …
CorrI2P: Deep image-to-point cloud registration via dense correspondence
Motivated by the intuition that the critical step of localizing a 2D image in the corresponding
3D point cloud is establishing 2D-3D correspondence between them, we propose the first …
3D point cloud is establishing 2D-3D correspondence between them, we propose the first …
2d3d-matr: 2d-3d matching transformer for detection-free registration between images and point clouds
The commonly adopted detect-then-match approach to registration finds difficulties in the
cross-modality cases due to the incompatible keypoint detection and inconsistent feature …
cross-modality cases due to the incompatible keypoint detection and inconsistent feature …
ATOP: An attention-to-optimization approach for automatic LiDAR-camera calibration via cross-modal object matching
Y Sun, J Li, Y Wang, X Xu, X Yang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Due to the difference of data modalities, it'sa very challenging task to find the feature
correspondences between 2D and 3D data in LiDAR-Camera calibration. In existing works …
correspondences between 2D and 3D data in LiDAR-Camera calibration. In existing works …