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Hand Pose Understanding With Large-Scale Photo-Realistic Rendering Dataset

文献类型：期刊论文

作者Deng, Xiaoming4; Zhang, Yinda3; Shi, Jian2; Zhu, Yuying4; Cheng, Dachuan5; Zuo, Dexin4; Cui, Zhaopeng7; Tan, Ping1,8; Chang, Liang6; Wang, Hongan4
刊名IEEE TRANSACTIONS ON IMAGE PROCESSING
出版日期2021
卷号30页码:4275-4290
关键词Three-dimensional displays Annotations Pose estimation Task analysis Color Image color analysis Rendering (computer graphics) Hand pose estimation photo-realistic synthetic dataset physical-based rendering multi-task CNN
ISSN号1057-7149
DOI10.1109/TIP.2021.3070439
通讯作者Deng, Xiaoming(xiaoming@iscas.ac.cn)
英文摘要Hand pose understanding is essential to applications such as human computer interaction and augmented reality. Recently, deep learning based methods achieve great progress in this problem. However, the lack of high-quality and large-scale dataset prevents the further improvement of hand pose related tasks such as 2D/3D hand pose from color and depth from color. In this paper, we develop a large-scale and high-quality synthetic dataset, PBRHand. The dataset contains millions of photo-realistic rendered hand images and various ground truths including pose, semantic segmentation, and depth. Based on the dataset, we firstly investigate the effect of rendering methods and used databases on the performance of three hand pose related tasks: 2D/3D hand pose from color, depth from color and 3D hand pose from depth. This study provides insights that photo-realistic rendering dataset is worthy of synthesizing and shows that our new dataset can improve the performance of the state-of-the-art on these tasks. This synthetic data also enables us to explore multi-task learning, while it is expensive to have all the ground truth available on real data. Evaluations show that our approach can achieve state-of-the-art or competitive performance on several public datasets.
资助项目National Key Research and Development Program of China[2019YFC1521100] ; Distinguished Young Researcher Program, Institute of Software, Chinese Academy of Sciences
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000640713600009
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Key Research and Development Program of China ; Distinguished Young Researcher Program, Institute of Software, Chinese Academy of Sciences
源URL[http://ir.ia.ac.cn/handle/173211/44497]  
专题模式识别国家重点实验室_三维可视计算
通讯作者Deng, Xiaoming
作者单位1.Simon Fraser Univ, Sch Comp Sci, Burnaby, BC V5A 1S6, Canada
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
3.Google, Mountain View, CA 94043 USA
4.Chinese Acad Sci, Inst Software, Beijing Key Lab Human Comp Interact, Beijing 100190, Peoples R China
5.Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100190, Peoples R China
6.Beijing Normal Univ, Sch Artificial Intelligence, Beijing 100875, Peoples R China
7.Zhejiang Univ, State Key Lab CAD&CG, Hangzhou 310058, Peoples R China
8.Alibaba, Hangzhou 310012, Peoples R China
推荐引用方式
GB/T 7714		 Deng, Xiaoming,Zhang, Yinda,Shi, Jian,et al. Hand Pose Understanding With Large-Scale Photo-Realistic Rendering Dataset[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2021,30:4275-4290.
APA Deng, Xiaoming.,Zhang, Yinda.,Shi, Jian.,Zhu, Yuying.,Cheng, Dachuan.,...&Wang, Hongan.(2021).Hand Pose Understanding With Large-Scale Photo-Realistic Rendering Dataset.IEEE TRANSACTIONS ON IMAGE PROCESSING,30,4275-4290.
MLA Deng, Xiaoming,et al."Hand Pose Understanding With Large-Scale Photo-Realistic Rendering Dataset".IEEE TRANSACTIONS ON IMAGE PROCESSING 30(2021):4275-4290.

入库方式： OAI收割

来源：自动化研究所

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