Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6864640 | Neurocomputing | 2018 | 38 Pages |
Abstract
We evaluate our framework on a facial landmark detection problem which is a typical structured output task. We show over two public challenging datasets (LFPW and HELEN) that our regularization scheme improves the generalization of deep neural networks and accelerates their training. The use of unlabeled data and label-only data is also explored, showing an additional improvement of the results. We provide an opensource implementation of our framework.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Soufiane Belharbi, Romain Hérault, Clément Chatelain, Sébastien Adam,