传统的人体姿态估计模型对于视角极为敏感,笔者的血泪经历也证明很难在不同视角的domain间做finetune。作者将元学习引入多视角的人体姿态估计任务中,通过将特征提取、跨视角融合权重、视角变换三者解耦,有效降低参数量以此大幅提升泛化性。方法的场景设定是具有一个rich的source domain和一个few labeled的target domain。三...
metafuse-package (1)datagenerator (3)metafuse (4)metafuse.l (6)Index8 metafuse-package Fused Lasso Approach in Regression Coefficient Clustering Description For each covariate,cluster its coefficient effects across different data sets during data integration.Supports Gaussian,binomial and Poisson ...
(Carlsbad, CA) to develop and commercialize its MetaFuse nanometal/polymer hybrid in the automotive, consumer electronics, and sporting goods markets, DuPont Engineering Polymers (Wilmington, DE) announced a similar long-term agreement with PowerMetal to extend the development....
AffineFuse 的表现超过了 NaiveFuse,验证了参数分解的有效性。而本文提出的 MetaFuse,在不同的数量时都超过了其他方法,验证了元学习算法可进一步增强模型的泛化性能。 图5:H36M数据集的2D结果 在H36M 和 Total Capture 数据集中,得到的 3D 结果分别如表1和表2所示。3D 姿态估计的准确度,使用真实 3D 坐标和预测...
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