Before revision: We explore the utility of harnessing auxiliary labels (e.g., facial expression) to impose ] ] geometric structure when training embedding models for one-shot learning (e. g., for face verification). We introduce novel geometric constraints on the embedding space learned by a deep model using either manually annotated or automatically detected auxiliary  labels.
After revision: We explore the utility of harnessing auxiliary labels (e.g., facial expression) to impose ] ] geometric constraints on the embedding space learned by a deep model using either manually annotated or automatically detected auxiliary labels.