CASIA OpenIR  > 多模态人工智能系统全国重点实验室  > 三维可视计算
Hand Pose Understanding With Large-Scale Photo-Realistic Rendering Dataset
Deng, Xiaoming1; Zhang, Yinda2; Shi, Jian3; Zhu, Yuying1; Cheng, Dachuan4; Zuo, Dexin1; Cui, Zhaopeng5; Tan, Ping6,7; Chang, Liang8; Wang, Hongan1
Source PublicationIEEE TRANSACTIONS ON IMAGE PROCESSING
ISSN1057-7149
2021
Volume30Pages:4275-4290
Corresponding AuthorDeng, Xiaoming(xiaoming@iscas.ac.cn)
AbstractHand 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.
KeywordThree-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
DOI10.1109/TIP.2021.3070439
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program of China[2019YFC1521100] ; Distinguished Young Researcher Program, Institute of Software, Chinese Academy of Sciences
Funding OrganizationNational Key Research and Development Program of China ; Distinguished Young Researcher Program, Institute of Software, Chinese Academy of Sciences
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000640713600009
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Sub direction classification计算机图形学与虚拟现实
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/44498
Collection多模态人工智能系统全国重点实验室_三维可视计算
Corresponding AuthorDeng, Xiaoming
Affiliation1.Chinese Acad Sci, Inst Software, Beijing Key Lab Human Comp Interact, Beijing 100190, Peoples R China
2.Google, Mountain View, CA 94043 USA
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100190, Peoples R China
5.Zhejiang Univ, State Key Lab CAD&CG, Hangzhou 310058, Peoples R China
6.Simon Fraser Univ, Sch Comp Sci, Burnaby, BC V5A 1S6, Canada
7.Alibaba, Hangzhou 310012, Peoples R China
8.Beijing Normal Univ, Sch Artificial Intelligence, Beijing 100875, Peoples R China
Recommended Citation
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.
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