TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction

doi:10.1145/3478513.3480486

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 三维可视计算

	TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction
	Liu, Yanchao 1,2,3; Guo, Jianwei1,4 ; Benes, Bedrich 5; Deussen, Oliver 6,7; Zhang, Xiaopeng1,4 ; Huang, Hui 2
发表期刊	ACM TRANSACTIONS ON GRAPHICS
ISSN	0730-0301
	2021-12-01
卷号	40 期号:6 页码:16
通讯作者	Huang, Hui(hhzhiyan@gmail.com)
摘要	We present TreePartNet, a neural network aimed at reconstructing tree geometry from point clouds obtained by scanning real trees. Our key idea is to learn a natural neural decomposition exploiting the assumption that a tree comprises locally cylindrical shapes. In particular, reconstruction is a two-step process. First, two networks are used to detect priors from the point clouds. One detects semantic branching points, and the other network is trained to learn a cylindrical representation of the branches. In the second step, we apply a neural merging module to reduce the cylindrical representation to a final set of generalized cylinders combined by branches. We demonstrate results of reconstructing realistic tree geometry for a variety of input models and with varying input point quality, e.g., noise, outliers, and incompleteness. We evaluate our approach extensively by using data from both synthetic and real trees and comparing it with alternative methods.
关键词	3D Reconstruction Procedural Modeling Deep Learning Optimization Procedural Generation Geometric Modeling
DOI	10.1145/3478513.3480486
关键词[WOS]	SHAPE ; MODELS
收录类别	SCI
语种	英语
资助项目	National Key RD Program[2018YFB2100602] ; NSFC[62172416] ; NSFC[61802406] ; NSFC[U2001206] ; Guangdong Talent Program[2019JC05X328] ; Guangdong Talent Program[00201509] ; Shenzhen Science and Technology Program[RCJC20200714114435012] ; Shenzhen Science and Technology Program[JCYJ20210324120213036] ; Shenzhen Science and Technology Program[JCYJ20180507182222355] ; NSF[10001387] ; Foundation for Food and Agriculture Research[602757] ; Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) ; National Engineering Laboratory for Big Data System Computing Technology ; DEGP Key Project[2018KZDXM058]
项目资助者	National Key RD Program ; NSFC ; Guangdong Talent Program ; Shenzhen Science and Technology Program ; NSF ; Foundation for Food and Agriculture Research ; Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) ; National Engineering Laboratory for Big Data System Computing Technology ; DEGP Key Project
WOS研究方向	Computer Science
WOS类目	Computer Science, Software Engineering
WOS记录号	WOS:000729846700037
出版者	ASSOC COMPUTING MACHINERY
七大方向——子方向分类	模式识别基础
引用统计	被引频次：15[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/47125
专题	多模态人工智能系统全国重点实验室_三维可视计算
通讯作者	Huang, Hui
作者单位	1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.Shenzhen Univ, Shenzhen, Guangdong, Peoples R China 3.CASIA, NLPR, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Automat, NLPR, Beijing, Peoples R China 5.Purdue Univ, W Lafayette, IN 47907 USA 6.SIAT & Univ Konstanz, Shenzhen, Guangdong, Peoples R China 7.Univ Konstanz, Constance, Germany
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Liu, Yanchao,Guo, Jianwei,Benes, Bedrich,et al. TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction[J]. ACM TRANSACTIONS ON GRAPHICS,2021,40(6):16.
APA	Liu, Yanchao,Guo, Jianwei,Benes, Bedrich,Deussen, Oliver,Zhang, Xiaopeng,&Huang, Hui.(2021).TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction.ACM TRANSACTIONS ON GRAPHICS,40(6),16.
MLA	Liu, Yanchao,et al."TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction".ACM TRANSACTIONS ON GRAPHICS 40.6(2021):16.