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Found 8 papers, 6 papers with code
Correspondence Matrices are Underrated
The loss functions that are optimized in these networks are based on the error in the transformation parameters.
MaskNet: A Fully-Convolutional Network to Estimate Inlier Points
We demonstrate these improvements on synthetic and real-world datasets.
One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment
We perform extensive simulation and real-world experiments to validate the efficacy of our approach and compare the performance with state-of-art approaches.
Globally optimal registration of noisy point clouds
Registration of 3D point clouds is a fundamental task in several applications of robotics and computer vision.
PCRNet: Point Cloud Registration Network using PointNet Encoding
PointNet has recently emerged as a popular representation for unstructured point cloud data, allowing application of deep learning to tasks such as object detection, segmentation and shape completion.
PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
To date, the successful application of PointNet to point cloud registration has remained elusive.
A Multi-Domain Feature Learning Method for Visual Place Recognition
Visual Place Recognition (VPR) is an important component in both computer vision and robotics applications, thanks to its ability to determine whether a place has been visited and where specifically.
MRS-VPR: a multi-resolution sampling based global visual place recognition method
We propose MRS-VPR, a multi-resolution, sampling-based place recognition method, which can significantly improve the matching efficiency and accuracy in sequential matching.
