Adaptive Graphical Model Network for 2D Handpose Estimation

18 Sep 2019Deying KongYifei ChenHaoyu MaXiangyi YanXiaohui Xie

In this paper, we propose a new architecture called Adaptive Graphical Model Network (AGMN) to tackle the task of 2D hand pose estimation from a monocular RGB image. The AGMN consists of two branches of deep convolutional neural networks for calculating unary and pairwise potential functions, followed by a graphical model inference module for integrating unary and pairwise potentials... (read more)

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