Pose-LDM generates occluded in-bed images from keypoints to augment training data, achieving top accuracy under severe occlusion compared to other augmentation methods.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A Transformer-based conditional generative model augments skeleton action datasets by synthesizing high-fidelity sequences, improving recognition accuracy in few-shot and full-data regimes on HumanAct12 and NTU-VIBE.
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Geometry-Conditioned Diffusion for Occlusion-Robust In-Bed Pose Estimation
Pose-LDM generates occluded in-bed images from keypoints to augment training data, achieving top accuracy under severe occlusion compared to other augmentation methods.
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Generative Data Augmentation for Skeleton Action Recognition
A Transformer-based conditional generative model augments skeleton action datasets by synthesizing high-fidelity sequences, improving recognition accuracy in few-shot and full-data regimes on HumanAct12 and NTU-VIBE.