… for face representation learning. Our method bases on a new structure of deep convolutional
neural network (called Pyramid CNN) with supervised learning signals in the form of face …

… to learn a set of high-level feature representations through deep learning, referred to as
Deep … Differently, in this paper we propose to learn highlevel face identity features with deep …

… features, we learn face representations using two CNN architectures described above.
To our knowledge, we are the first to use deep CNNs for NIR-VIS face recognition. The main …

… are: • A method for learning a universal face representation by associating features with …
• A training strategy to effectively combine synthesized data to train a face representation …

… for traditional face recognition algorithms. This paper proposes a … deep learning framework
to jointly learn face representation using multimodal information. The proposed deep learning …

… that deep learning based face representation is robust to misalignment and able to
tolerate facial feature localization errors up to 10% of the interocular distance. (iv) The VGG-Face …

… We apply the proposed AdaCos loss to large-scale face verification and identification … that
training deep neural networks with the AdaCos loss is stable and able to achieve high face …

… In this paper, we show that it can be well solved with deep learning and using both face
identification and verification signals as supervision. The Deep IDentification-verification features …

… in the literature do not use deep learning, such as SIFT, LBP [… with deep learning and the
speed of SRC for face recognition. … [21] of DeepFace used deep CNNs to classify a large face …

… breakthroughs of DeepFace and DeepID. Since then, deep learning technique, characterized
by the hierarchical architecture to stitch together pixels into invariant face representation, …