A Mixture of Personalized Experts for Human Affect Estimation
We investigate the personalization of deep convolutional neural networks for facial expression analysis from still images. While prior work has focused on population-based (“one-size-fits-all”) approaches, we formulate and construct personalized models via a mixture of experts and supervised domain...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Book |
| Language: | English |
| Published: |
Springer International Publishing
2021
|
| Online Access: | https://hdl.handle.net/1721.1/129494 |