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arXiv · 2010.10451

Tilting at windmills: Data augmentation for deep pose estimation does not help with occlusions

Rafal Pytel·Osman Semih Kayhan·Jan C. van Gemert
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Abstract

Occlusion degrades the performance of human pose estimation. In this paper, we introduce targeted keypoint and body part occlusion attacks. The effects of the attacks are systematically analyzed on the best performing methods. In addition, we propose occlusion specific data augmentation techniques against keypoint and part attacks. Our extensive experiments show that human pose estimation methods are not robust to occlusion and data augmentation does not solve the occlusion problems.

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Rafal Pytel, Osman Semih Kayhan, Jan C. van Gemert. 2020-10-20. Tilting at windmills: Data augmentation for deep pose estimation does not help with occlusions. https://arxiv.org/abs/2010.10451

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