文件名称：复杂环境下的人脸识别Deep Learning Face Attributes in the Wild
文件大小：6.01MB
文件格式：PDF
更新时间：2021-04-28 16:19:58
Deep learning, Face Attribute, Wild
Predicting face attributes in the wild is challenging due to complex face variations. We propose a novel deep learning framework for attribute prediction in the wild. It cascades two CNNs, LNet and ANet, which are fine- tuned jointly with attribute tags, but pre-trained differently. LNet is pre-trained by massive general object categories for face localization, while ANet is pre-trained by massive face identities for attribute prediction. This framework not only outperforms the state-of-the-art with a large margin, but also reveals valuable facts on learning face representation.