A controllable generative augmentation approach synthesizes diverse pose videos from indoor and outdoor datasets to improve model performance on unseen domains in 3D human pose estimation.
A dual- augmentor framework for domain generalization in 3d human pose estimation
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Enhancing Domain Generalization in 3D Human Pose Estimation through Controllable Generative Augmentation
A controllable generative augmentation approach synthesizes diverse pose videos from indoor and outdoor datasets to improve model performance on unseen domains in 3D human pose estimation.