Custom Structure Preservation in Face Aging

摘要

In this work, we propose a novel architecture for face age editing that can produce structural modifications while maintaining relevant details present in the original image. We disentangle the style and content of the input image and propose a new decoder network that adopts a style-based strategy to combine the style and content representations of the input image while conditioning the output on the target age. Furthermore, we go beyond existing aging methods by allowing the users to adjust the degree of structure preservation in the input image at inference time. To this aim, we introduce a masking mechanism, termed Custom Structure Preservation (CUSP) module, that distinguishes relevant regions in the input image that should be preserved from those where details are irrelevant for the task. This mechanism does not require any additional supervision. Finally, we show that our method outperforms prior art on three datasets and demonstrate the effectiveness of our strategy to adjust structure preservation.