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Pose Estimation

277 bytes removed, 7 June
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Pose estimation is widely used in applications such as motion capture, human-computer interaction, augmented reality, and robotics. The process typically involves training machine learning models on large datasets of annotated images to accurately identify and locate the keypoints.
These models can range from simple algorithms for 2D pose estimation to more complex systems that infer 3D poses. Recent advances in deep learning have significantly improved the accuracy and robustness of pose estimation systems, enabling their use in real-time applications.
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