ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones
被引:6
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作者:
论文数: 引用数:
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机构:
An, Shan
[1
,2
]
论文数: 引用数:
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机构:
Che, Guangfu
[1
]
论文数: 引用数:
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机构:
Guo, Jinghao
[1
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Zhu, Haogang
论文数: 0引用数: 0
h-index: 0
机构:
Beihang Univ, State Key Lab Software Dev Environm, Beijing, Peoples R China
Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing, Peoples R ChinaJD COM Inc, Beijing, Peoples R China
Zhu, Haogang
[2
,3
]
Ye, Junjie
论文数: 0引用数: 0
h-index: 0
机构:
JD COM Inc, Beijing, Peoples R ChinaJD COM Inc, Beijing, Peoples R China
Ye, Junjie
[1
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Zhou, Fangru
论文数: 0引用数: 0
h-index: 0
机构:
JD COM Inc, Beijing, Peoples R ChinaJD COM Inc, Beijing, Peoples R China
Zhou, Fangru
[1
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Zhu, Zhaoqi
论文数: 0引用数: 0
h-index: 0
机构:
JD COM Inc, Beijing, Peoples R ChinaJD COM Inc, Beijing, Peoples R China
Zhu, Zhaoqi
[1
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Wei, Dong
论文数: 0引用数: 0
h-index: 0
机构:
JD COM Inc, Beijing, Peoples R ChinaJD COM Inc, Beijing, Peoples R China
Wei, Dong
[1
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Liu, Aishan
论文数: 0引用数: 0
h-index: 0
机构:
Beihang Univ, State Key Lab Software Dev Environm, Beijing, Peoples R ChinaJD COM Inc, Beijing, Peoples R China
Liu, Aishan
[2
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Zhang, Wei
论文数: 0引用数: 0
h-index: 0
机构:
JD COM Inc, Beijing, Peoples R ChinaJD COM Inc, Beijing, Peoples R China
Zhang, Wei
[1
]
机构:
[1] JD COM Inc, Beijing, Peoples R China
[2] Beihang Univ, State Key Lab Software Dev Environm, Beijing, Peoples R China
[3] Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing, Peoples R China
来源:
PROCEEDINGS OF THE 29TH ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA, MM 2021
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2021年
Virtual try-on technology enables users to try various fashion items using augmented reality and provides a convenient online shopping experience. However, most previous works focus on the virtual try-on for clothes while neglecting that for shoes, which is also a promising task. To this concern, this work proposes a real-time augmented reality virtual shoe try-on system for smartphones, namely ARShoe. Specifically, ARShoe adopts a novel multi-branch network to realize pose estimation and segmentation simultaneously. A solution to generate realistic 3D shoe model occlusion during the try-on process is presented. To achieve a smooth and stable tryon effect, this work further develop a novel stabilization method. Moreover, for training and evaluation, we construct the very first large-scale foot benchmark with multiple virtual shoe try-on taskrelated labels annotated. Exhaustive experiments on our newly constructed benchmark demonstrate the satisfying performance of ARShoe. Practical tests on common smartphones validate the real-time performance and stabilization of the proposed approach.