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题名

Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation

作者
DOI
发表日期
2023
ISSN
1063-6919
ISBN
979-8-3503-0130-4
会议录名称
页码
5537-5546
会议日期
17-24 June 2023
会议地点
Vancouver, BC, Canada
摘要
A central challenge in human pose estimation, as well as in many other machine learning and prediction tasks, is the generalization problem. The learned network does not have the capability to characterize the prediction error, generate feedback information from the test sample, and correct the prediction error on the fly for each individual test sample, which results in degraded performance in generalization. In this work, we introduce a self-correctable and adaptable inference (SCAI) method to address the generalization challenge of network prediction and use human pose estimation as an example to demonstrate its effectiveness and performance. We learn a correction network to correct the prediction result conditioned by a fitness feedback error. This feedback error is generated by a learned fitness feedback network which maps the prediction result to the original input domain and compares it against the original input. Interestingly, we find that this self-referential feedback error is highly correlated with the actual prediction error. This strong correlation suggests that we can use this error as feedback to guide the correction process. It can be also used as a loss function to quickly adapt and optimize the correction network during the inference process. Our extensive experimental results on human pose estimation demonstrate that the proposed SCAI method is able to significantly improve the generalization capability and performance of human pose estimation.
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第一
相关链接[IEEE记录]
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WOS记录号
WOS:001058542605084
来源库
IEEE
全文链接https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10205053
引用统计
被引频次[WOS]:3
成果类型会议论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/559173
专题工学院_电子与电气工程系
作者单位
Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
第一作者单位电子与电气工程系
第一作者的第一单位电子与电气工程系
推荐引用方式
GB/T 7714
Zhehan Kan,Shuoshuo Chen,Ce Zhang,et al. Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation[C],2023:5537-5546.
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