We lay the groundwork for research in the algorithmic comprehension of infant faces, in anticipation of applications from healthcare to psychology, especially in the early prediction of developmental disorders. Specifically, we introduce the first-ever dataset of infant faces annotated with facial landmark coordinates and pose attributes, demonstrate the inadequacies of existing facial landmark estimation algorithms in the infant domain, and train new state-of-the-art models that significantly improve upon those algorithms using domain adaptation techniques. We touch on the closely related task of facial detection for infants, and also on a challenging case study of infrared baby monitor images gathered by our lab as part of in-field research into the aforementioned developmental issues.

翻译：我们为婴儿面部算法理解的研究打下基础,以预测从保健到心理的应用,特别是早期发育障碍的预测。 具体地说,我们引入了有史以来第一个婴儿面部标记的数据集,配有面部标志坐标和属性,表明婴儿领域现有面部标志估计算法的不足,并培训新的最先进的模型,这些模型利用域适应技术大大改进了这些算法。 我们触及了与婴儿面部检测密切相关的任务,以及我们实验室收集的红外线婴儿监测图像的富有挑战性的个案研究,作为上述发展问题实地研究的一部分。