Forecasting future poses can be done accurately by encoding joint trajectories with a discrete cosine transform and feeding the coefficients to a graph network that learns joint dependencies automatically.
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Learning Trajectory Dependencies for Human Motion Prediction
Forecasting future poses can be done accurately by encoding joint trajectories with a discrete cosine transform and feeding the coefficients to a graph network that learns joint dependencies automatically.