Temporal Continual Learning with Prior Compensation for Human Motion Prediction

Neural Information Processing Systems 

To better preserve prior information, we introduce the Prior Compensation Factor (PCF). We incorporate it into the model training to compensate for the lost prior information. Furthermore, we derive a more reasonable optimization objective through theoretical derivation.

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