Search Results for author:
Found 2 papers, 1 papers with code
Adversarial Attention for Human Motion Synthesis
Furthermore, we show that we can improve the classification performance of deep learning models in cases where there is inadequate real data, by supplementing existing datasets with synthetic motions.
Towards Explainable, Privacy-Preserved Human-Motion Affect Recognition
We evaluate the effectiveness of our method to existing methods at recognizing emotions using both 3D temporal joint signals and manually extracted features.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
