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Advances in Human Pose Estimation by nkaintura388 is a document available to read on EtoBox.

The research paper reviews current methods for human pose estimation, analyzing 15 studies that highlight advancements in single-person, multi-person, and 3D pose estimation using both traditional and deep learning approaches. It emphasizes the significant accuracy improvements brought by deep learning techniques and the importance of large-scale datasets in this field. The paper also discusses various applications of pose estimation in sectors like sports, healthcare, and robotics.

Author
nkaintura388
Language
EN