Robust point cloud registration framework based on deep graph matching
Abstract 3D point cloud registration is a fundamental problem in computer vision and
robotics. Recently, learning-based point cloud registration methods have made great …
robotics. Recently, learning-based point cloud registration methods have made great …
Deepgmr: Learning latent gaussian mixture models for registration
Point cloud registration is a fundamental problem in 3D computer vision, graphics and
robotics. For the last few decades, existing registration algorithms have struggled in …
robotics. For the last few decades, existing registration algorithms have struggled in …
[HTML][HTML] SYNAPSE: An international roadmap to large brain imaging
APJ Stampfl, Z Liu, J Hu, K Sawada, H Takano… - Physics Reports, 2023 - Elsevier
Since 2020, synchrotron radiation facilities in several Asia-Pacific countries have been
collaborating in a major project called “SYNAPSE”(Synchrotrons for Neuroscience: an Asia …
collaborating in a major project called “SYNAPSE”(Synchrotrons for Neuroscience: an Asia …
Unsupervised deep probabilistic approach for partial point cloud registration
Deep point cloud registration methods face challenges to partial overlaps and rely on
labeled data. To address these issues, we propose UDPReg, an unsupervised deep …
labeled data. To address these issues, we propose UDPReg, an unsupervised deep …
PANet: A point-attention based multi-scale feature fusion network for point cloud registration
Point cloud registration is a critical task in many 3-D computer vision studies, aiming to find a
rigid transformation that aligns one point cloud with another. In this article, we propose a …
rigid transformation that aligns one point cloud with another. In this article, we propose a …
Patchwork: Concentric zone-based region-wise ground segmentation with ground likelihood estimation using a 3D LiDAR sensor
Ground segmentation is crucial for terrestrial mobile platforms to perform navigation or
neighboring object recognition. Unfortunately, the ground is not flat, as it features steep …
neighboring object recognition. Unfortunately, the ground is not flat, as it features steep …
Spaghetti: Editing implicit shapes through part aware generation
Neural implicit fields are quickly emerging as an attractive representation for learning based
techniques. However, adopting them for 3D shape modeling and editing is challenging. We …
techniques. However, adopting them for 3D shape modeling and editing is challenging. We …
Approximate differentiable rendering with algebraic surfaces
Differentiable renderers provide a direct mathematical link between an object's 3D
representation and images of that object. In this work, we develop an approximate …
representation and images of that object. In this work, we develop an approximate …
3D local features for direct pairwise registration
We present a novel, data driven approach for solving the problem of registration of two point
cloud scans. Our approach is direct in the sense that a single pair of corresponding local …
cloud scans. Our approach is direct in the sense that a single pair of corresponding local …