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Buffer: Balancing accuracy, efficiency, and generalizability in point cloud registration
An ideal point cloud registration framework should have superior accuracy, acceptable
efficiency, and strong generalizability. However, this is highly challenging since existing …
efficiency, and strong generalizability. However, this is highly challenging since existing …
[PDF][PDF] A comprehensive survey and taxonomy on point cloud registration based on deep learning
Point cloud registration (PCR) involves determining a rigid transformation that aligns one
point cloud to another. Despite the plethora of outstanding deep learning (DL)-based …
point cloud to another. Despite the plethora of outstanding deep learning (DL)-based …
Evolutionary multitasking descriptor optimization for point cloud registration
Point cloud registration is an important task for other point cloud tasks. Feature-based
methods are widely adopted for their speed and efficiency in point cloud registration. The …
methods are widely adopted for their speed and efficiency in point cloud registration. The …
Sira-pcr: Sim-to-real adaptation for 3d point cloud registration
Point cloud registration is essential for many applications. However, existing real datasets
require extremely tedious and costly annotations, yet may not provide accurate camera …
require extremely tedious and costly annotations, yet may not provide accurate camera …
Robust multiview point cloud registration with reliable pose graph initialization and history reweighting
In this paper, we present a new method for the multiview registration of point cloud. Previous
multiview registration methods rely on exhaustive pairwise registration to construct a …
multiview registration methods rely on exhaustive pairwise registration to construct a …
Incremental registration towards large-scale heterogeneous point clouds by hierarchical graph matching
The increasing availability of point cloud acquisition techniques makes it possible to
significantly increase 3D observation capacity by the registration of multi-sensor, multi …
significantly increase 3D observation capacity by the registration of multi-sensor, multi …
PointDifformer: Robust point cloud registration with neural diffusion and transformer
Point cloud registration is a fundamental technique in 3-D computer vision with applications
in graphics, autonomous driving, and robotics. However, registration tasks under …
in graphics, autonomous driving, and robotics. However, registration tasks under …
Pointreggpt: Boosting 3d point cloud registration using generative point-cloud pairs for training
Data plays a crucial role in training learning-based methods for 3D point cloud registration.
However, the real-world dataset is expensive to build, while rendering-based synthetic data …
However, the real-world dataset is expensive to build, while rendering-based synthetic data …
Mac: Maximal cliques for 3d registration
This paper presents a 3D registration method with maximal cliques (MAC) for 3D point cloud
registration (PCR). The key insight is to loosen the previous maximum clique constraint and …
registration (PCR). The key insight is to loosen the previous maximum clique constraint and …
Deep learning-based point cloud registration: A comprehensive investigation
X Cheng, X Liu, J Li, W Zhou - International Journal of Remote …, 2024 - Taylor & Francis
Point cloud registration is the process of aligning and merging multiple point clouds into a
same coordinate system. It has many applications in computer vision, robotics, 3D …
same coordinate system. It has many applications in computer vision, robotics, 3D …