Shypd.aiThe largest open index of AI toolsHeadPoseEstimation-WHENet is a Coding & Development tool that provides real-time, fine-grained head pose estimation. It predicts Euler angles across a wide range of head yaws from a single RGB image, applicable to full viewpoints.
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HeadPoseEstimation-WHENet is an end-to-end head-pose estimation network designed for real-time, fine-grained prediction of Euler angles across the full range of head yaws from a single RGB image. Unlike many existing methods that perform well only for frontal views, WHENet targets head poses from all viewpoints, making it suitable for applications in autonomous driving and retail. The network builds on multi-loss approaches with adapted loss functions and training strategies for wide-range estimation. It also uniquely extracts ground truth labelings of anterior views from a panoptic dataset. WHENet is compact and efficient, making it suitable for mobile devices and applications, and meets or beats state-of-the-art methods for frontal head pose estimation.
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