SHaRPose: Sparse High-Resolution Representation for Human Pose Estimation
Xiaoqi An,
Lin Zhao,
Chen Gong
et al.
Abstract:High-resolution representation is essential for achieving good performance in human pose estimation models. To obtain such features, existing works utilize high-resolution input images or fine-grained image tokens. However, this dense high-resolution representation brings a significant computational burden. In this paper, we address the following question: "Only sparse human keypoint locations are detected for human pose estimation, is it really necessary to describe the whole image in a dense, high-resolution… Show more
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