178 citations · 189 across the 7 of their papers we have counts for
7 papers
MSECNet: Accurate and Robust Normal Estimation for 3D Point Clouds by Multi-Scale Edge Conditioning
Haoyi Xiu, Xin Liu, Weimin Wang +2
Estimating surface normals from 3D point clouds is critical for various applications, including surface reconstruction and rendering. While existing methods for normal estimation p…
Diffusion Unit: Interpretable Edge Enhancement and Suppression Learning for 3D Point Cloud Segmentation
Haoyi Xiu, Xin Liu, Weimin Wang +4
3D point clouds are discrete samples of continuous surfaces which can be used for various applications. However, the lack of true connectivity information, i.e., edge information,…
Enhancing Local Geometry Learning for 3D Point Cloud via Decoupling Convolution
Haoyi Xiu, Xin Liu, Weimin Wang +4
Modeling the local surface geometry is challenging in 3D point cloud understanding due to the lack of connectivity information. Most prior works model local geometry using various…
Enhancing Local Feature Learning Using Diffusion for 3D Point Cloud Understanding
Haoyi Xiu, Xin Liu, Weimin Wang +4
Learning point clouds is challenging due to the lack of connectivity information, i.e., edges. Although existing edge-aware methods can improve the performance by modeling edges, h…
Enhancing Local Feature Learning for 3D Point Cloud Processing using Unary-Pairwise Attention
Haoyi Xiu, Xin Liu, Weimin Wang +4
We present a simple but effective attention named the unary-pairwise attention (UPA) for modeling the relationship between 3D point clouds. Our idea is motivated by the analysis th…
Learning from Multimodal and Multitemporal Earth Observation Data for Building Damage Mapping
Bruno Adriano, Naoto Yokoya, Junshi Xia +4
Earth observation technologies, such as optical imaging and synthetic aperture radar (SAR), provide excellent means to monitor ever-growing urban environments continuously. Notably…
Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets
Kenji Enomoto, Ken Sakurada, Weimin Wang +4
In this paper, we propose a method for cloud removal from visible light RGB satellite images by extending the conditional Generative Adversarial Networks (cGANs) from RGB images to…