BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs

Araceli Morales, Antònia Alomar, Antonio R. Porras, Marius George Linguraru, Gemma Piella, Federico M. Sukno

Abstract: Highlights•A specifically designed 3D face reconstruction system is needed to target babies.•We present the BabyNet, which is constructed is constructed using graph neural networks.•We use transfer learning to extract meaningful features from the input images.•The BabyNet outperforms deep learning-based approached trained with adult data.•The BabyNet outperforms classical model-fitting methods, even when baby-specific 3D morphable model (e.g. BabyFM) is used.