Improve human pose estimation using distance and direction of keypoints with Ji
Improve human pose estimation using distance and direction of keypoints with Ji
2D Human Pose Estimation with Explicit Anatomical Keypoints Structure Constraints
arXiv paper abstract https://arxiv.org/abs/2212.02163
arXiv PDF paper https://arxiv.org/pdf/2212.02163.pdf
Recently, human pose estimation mainly focuses on how to design a more effective and better deep network structure as human features extractor, and
most designed feature extraction networks only introduce the position of each anatomical keypoint to guide their training process.
... found that some human anatomical keypoints kept their topology invariance, which can help to localize them more accurately when detecting the keypoints on the feature map.
... present a novel 2D human pose estimation method with explicit anatomical keypoints structure constraints, which introduces the topology constraint term that consisting of the differences between the distance and direction of the keypoint-to-keypoint and their groundtruth in the loss object.
... proposed model can be plugged in the most existing bottom-up or top-down human pose estimation methods and improve their performance.
... show that ... methods perform favorably against the most existing bottom-up and top-down human pose estimation methods ...
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