6DRepNet
Visit Tool6DRepNet is an open-source Pytorch implementation for unconstrained head pose estimation, utilizing a 6D rotation representation. It significantly outperforms state-of-the-art methods in accuracy.
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6DRepNet is an open-source Pytorch implementation for unconstrained head pose estimation, utilizing a 6D rotation representation. It significantly outperforms state-of-the-art methods in accuracy.
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About
6DRepNet is the official Pytorch implementation of a novel method for unconstrained end-to-end head pose estimation. It addresses the challenge of ambiguous rotation labels by introducing a continuous 6D rotation matrix representation for robust direct regression, enabling the learning of full rotation appearance. Unlike previous approaches that restrict pose prediction to narrow angles, 6DRepNet achieves satisfactory results across a full range of head orientations. The tool also incorporates a geodesic distance-based loss function to penalize the network based on manifold geometry. Experiments on public datasets like AFLW2000 and BIWI demonstrate that 6DRepNet significantly surpasses other state-of-the-art methods by up to 20% in accuracy.
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