Title | Sparse Local Patch Transformer for Robust Face Alignment and Landmarks Inherent Relation Learning |
Author | |
Corresponding Author | Jianguo Zhang; Min Xu |
Joint first author | Jiahao Xia |
DOI | |
Publication Years | 2022
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Conference Name | Conference on Computer Vision and Pattern Recognition (CVPR)
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ISSN | 1063-6919
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ISBN | 978-1-6654-6947-0
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Source Title | |
Volume | 2022-June
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Pages | 4042-4051
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Conference Date | 18-24 June 2022
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Conference Place | New Orleans, LA, USA
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Publication Place | 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
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Publisher | |
Abstract | Heatmap regression methods have dominated face alignment area in recent years while they ignore the inherent relation between different landmarks. In this paper, we propose a Sparse Local Patch Transformer (SLPT) for learning the inherent relation. The SLPT generates the representation of each single landmark from a local patch and aggregates them by an adaptive inherent relation based on the attention mechanism. The subpixel coordinate of each landmark is predicted independently based on the aggregated feature. Moreover, a coarse-to-fine framework is further introduced to incorporate with the SLPT, which enables the initial landmarks to gradually converge to the target facial landmarks using fine-grained features from dynamically resized local patches. Extensive experiments carried out on three popular benchmarks, including WFLW, 300W and COFW, demonstrate that the proposed method works at the state-of-the-art level with much less computational complexity by learning the inherent relation between facial landmarks. The code is available at the project website(1). |
Keywords | |
SUSTech Authorship | Corresponding
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Language | English
|
URL | [Source Record] |
Indexed By | |
Funding Project | program of China Scholarships Council[202006130004]
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WOS Research Area | Computer Science
; Imaging Science & Photographic Technology
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WOS Subject | Computer Science, Artificial Intelligence
; Imaging Science & Photographic Technology
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WOS Accession No | WOS:000867754204030
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EI Accession Number | 20224613120153
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Data Source | IEEE
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PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9879432 |
Citation statistics |
Cited Times [WOS]:0
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Document Type | Conference paper |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/406480 |
Department | Southern University of Science and Technology 工学院_计算机科学与工程系 |
Affiliation | 1.Faculty of Engineering and IT, University of Technology Sydney 2.Dept. of Comp. Sci. and Eng., Southern University of Science and Technology 3.CaimCar |
Corresponding Author Affilication | Southern University of Science and Technology |
Recommended Citation GB/T 7714 |
Jiahao Xia,Weiwei Qu,Wenjian Huang,et al. Sparse Local Patch Transformer for Robust Face Alignment and Landmarks Inherent Relation Learning[C]. 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA:IEEE COMPUTER SOC,2022:4042-4051.
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Files in This Item: | ||||||
File Name/Size | DocType | Version | Access | License | ||
Xia_Sparse_Local_Pat(4509KB) | Restricted Access | -- |
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