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Found 5 papers, 3 papers with code
Joint Pose and Shape Estimation of Vehicles from LiDAR Data
We address the problem of estimating the pose and shape of vehicles from LiDAR scans, a common problem faced by the autonomous vehicle community.
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.
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.
Aligning Across Large Gaps in Time
We present a method of temporally-invariant image registration for outdoor scenes, with invariance across time of day, across seasonal variations, and across decade-long periods, for low- and high-texture scenes.
