Encoding discriminative representation for point cloud semantic segmentation
نویسندگان
چکیده
منابع مشابه
Context Encoding for Semantic Segmentation
Recent work has made significant progress in improving spatial resolution for pixelwise labeling with Fully Convolutional Network (FCN) framework by employing Dilated/Atrous convolution, utilizing multi-scale features and refining boundaries. In this paper, we explore the impact of global contextual information in semantic segmentation by introducing the Context Encoding Module, which captures ...
متن کاملUnstructured Point Cloud Semantic Labeling Using Deep Segmentation Networks
In this work, we describe a new, general, and efficient method for unstructured point cloud labeling. As the question of efficiently using deep Convolutional Neural Networks (CNNs) on 3D data is still a pending issue, we propose a framework which applies CNNs on multiple 2D image views (or snapshots) of the point cloud. The approach consists in three core ideas. (i) We pick many suitable snapsh...
متن کاملLarge-scale Point Cloud Semantic Segmentation with Superpoint Graphs
We propose a novel deep learning-based framework to tackle the challenge of semantic segmentation of largescale point clouds of millions of points. We argue that the organization of 3D point clouds can be efficiently captured by a structure called superpoint graph (SPG), derived from a partition of the scanned scene into geometrically homogeneous elements. SPGs offer a compact yet rich represen...
متن کاملInteractive Learning for Point-Cloud Motion Segmentation
Segmenting a moving foreground (fg) from its background (bg) is a fundamental step in many Machine Vision and Computer Graphics applications. Nevertheless, hardly any attempts have been made to tackle this problem in dynamic 3D scanned scenes. Scanned dynamic scenes are typically challenging due to noise and large missing parts. Here, we present a novel approach for motion segmentation in dynam...
متن کاملCRF Based Point Cloud Segmentation
Since devices to capture point clouds easily are relatively recent (Kinect), there has not been much research into segmenting out objects from a point cloud. Previous work in the segmentation of 3d point cloud scenes has usually involved the extracting geometric primitives using features like normals and curvatures [2, 3]. Other research has focused on segmenting out a single object foreground ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Electronics Letters
سال: 2021
ISSN: 0013-5194,1350-911X
DOI: 10.1049/ell2.12118