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微软研究院的最新大作。We describe two new approaches to human pose estimation. Both can quickly and accurately predict the 3D positions of body jointsfromasingledepthimage,withoutusinganytemporalinformation.Thekeytobothapproachesistheuseofalarge,realistic, and highly varied synthetic set of training images. This allows us to learn models that are largely invariant to factors such as pose, body shape, field-of-view cropping, and clothing. Our first approach employs an intermediate body parts representation,
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