Explicitly guided information interaction network for cross-modal point cloud completion
In this paper, we explore a novel framework, EGIInet (Explicitly Guided Information
Interaction Network), a model for View-guided Point cloud Completion (ViPC) task, which …
Interaction Network), a model for View-guided Point cloud Completion (ViPC) task, which …
[HTML][HTML] A benchmark approach and dataset for large-scale lane mapping from MLS point clouds
Accurate lane maps with semantics are crucial for various applications, such as high-
definition maps (HD Maps), intelligent transportation systems (ITS), and digital twins. Manual …
definition maps (HD Maps), intelligent transportation systems (ITS), and digital twins. Manual …
Reverse2complete: Unpaired multimodal point cloud completion via guided diffusion
Unpaired point cloud completion involves filling in missing parts of a point cloud without
requiring partial-complete correspondence. Meanwhile, since point cloud completion is an ill …
requiring partial-complete correspondence. Meanwhile, since point cloud completion is an ill …
Self-supervised 3D Point Cloud Completion via Multi-view Adversarial Learning
In real-world scenarios, scanned point clouds are often incomplete due to occlusion issues.
The task of self-supervised point cloud completion involves reconstructing missing regions …
The task of self-supervised point cloud completion involves reconstructing missing regions …
Voting-based patch sequence autoregression network for adaptive point cloud completion
H Wu, Y Miao - Computers & Graphics, 2024 - Elsevier
Point cloud completion aims to estimate the whole shapes of objects from their partial scans,
and one of the main obstacles that prevents current methods from being applied in real …
and one of the main obstacles that prevents current methods from being applied in real …
[HTML][HTML] Stage-Aware Interaction Network for Point Cloud Completion
H Wu, Y Miao - Electronics, 2024 - mdpi.com
Point cloud completion aims to restore full shapes of objects from partial scans, and a typical
network pipeline is AutoEncoder, which has coarse-to-fine refinement modules. Although …
network pipeline is AutoEncoder, which has coarse-to-fine refinement modules. Although …
LMA-Net: Lightweight Multiple Attention Network for Multi-source Heterogeneous Pulmonary CXR Segmentation
T Mamut, L Meng, Z Pei, T Weng, Q Han, K Wu… - IEEE …, 2024 - ieeexplore.ieee.org
The automatic pulmonary segmentation for chest X-ray (CXR) plays an important role in
assisting diagnosis. Many deep learning methods have the problems of high computational …
assisting diagnosis. Many deep learning methods have the problems of high computational …
INRet: A General Framework for Accurate Retrieval of INRs for Shapes
Implicit neural representations (INRs) have become an important method for encoding
various data types, such as 3D objects or scenes, images, and videos. They have proven to …
various data types, such as 3D objects or scenes, images, and videos. They have proven to …
A benchmark approach and dataset for large-scale lane mapping from MLS point clouds
Accurate lane maps with semantics are crucial for various applications, such as high-
definition maps (HD Maps), intelligent transportation systems (ITS), and digital twins. Manual …
definition maps (HD Maps), intelligent transportation systems (ITS), and digital twins. Manual …
Weakly supervised label learning flows
Supervised learning usually requires a large amount of labeled data. However, attaining
ground-truth labels is costly for many tasks. Alternatively, weakly supervised methods learn …
ground-truth labels is costly for many tasks. Alternatively, weakly supervised methods learn …