Single-View 3D reconstruction: A Survey of deep learning methods

被引：72
作者：
Fahim, George [1 ,2 ]
Amin, Khalid [1 ]
Zarif, Sameh [1 ]
机构：
[1] Menoufia Univ, Fac Comp & Informat, Dept Informat Technol, Al Minufiyah, Egypt
[2] Int Acad Engn & Media Sci, Multimedia & Internet Dept, Giza, Egypt
来源：
COMPUTERS & GRAPHICS-UK | 2021年 / 94卷
关键词：
3D Machine learning; Geometric deep learning; 3D Synthesis; 3D Representations; Single-view 3D reconstruction; GENERATION; SHAPE;
D O I：
10.1016/j.cag.2020.12.004
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
The field of single-view 3D shape reconstruction and generation using deep learning techniques has seen rapid growth in the past five years. As the field is reaching a stage of maturity, a plethora of methods has been continuously proposed with the aim of pushing the state of research further. This article focuses on surveying the literature by classifying these methods according to the shape representation they use as an output. Specifically, it covers each method's main contributions, degree of supervision, training paradigm, and its relation to the whole body of literature. Additionally, this survey discusses common 3D datasets, loss functions, and evaluation metrics used in the field. Finally, it provides a thorough analysis and reflections on the current state of research and provides a summary of the open problems and possible future directions. This work is an effort to introduce the field of data-driven single-view 3D reconstruction to interested researchers while being comprehensive enough to act as a reference to those who already do research in the field. (C) 2021 Elsevier Ltd. All rights reserved.
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收藏
页码：164 / 190
页数：27
相关论文
共 124 条
[11]  
Chen W, 2019, ARXIV PREPRINT ARXIV
[12]  
Chen W, 2016, ADV NEUR IN, V29
[13]   Learning Implicit Fields for Generative Shape Modeling [J].
Chen, Zhiqin ;
Zhang, Hao .
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, :5932-5941
[14]   3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction [J].
Choy, Christopher B. ;
Xu, Danfei ;
Gwak, Jun Young ;
Chen, Kevin ;
Savarese, Silvio .
COMPUTER VISION - ECCV 2016, PT VIII, 2016, 9912 :628-644
[15]   Metro:: Measuring error on simplified surfaces [J].
Cignoni, P ;
Rocchini, C ;
Scopigno, R .
COMPUTER GRAPHICS FORUM, 1998, 17 (02) :167-174
[16]   Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesis [J].
Dai, Angela ;
Qi, Charles Ruizhongtai ;
Niessner, Matthias .
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017), 2017, :6545-6554
[17]  
Defferrard M, 2016, ADV NEUR IN, V29
[18]   3D Sketching using Multi-View Deep Volumetric Prediction [J].
Delanoy, Johanna ;
Aubry, Mathieu ;
Isola, Phillip ;
Efros, Alexei A. ;
Bousseau, Adrien .
PROCEEDINGS OF THE ACM ON COMPUTER GRAPHICS AND INTERACTIVE TECHNIQUES, 2018, 1 (01)
[19]  
Deng J, 2009, PROC CVPR IEEE, P248, DOI 10.1109/CVPRW.2009.5206848
[20]  
Deprelle T, 2019, ADV NEUR IN, V32
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