Decomposed Meta Batch Normalization for Fast Domain Adaptation in Face Recognition
Jianzhu Guo, Xiangyu Zhu, Zhen Lei, Stan Z. Li TIFS (IEEE Transactions on Information Forensics and Security) (Accepted) paper / This paper proposes a novel training remedy by decomposing the model into the weight parameters and the BN statistics in the training phase. Based on decomposing, we design a novel framework via meta-learning, called Decomposed Meta Batch Normalization (DMBN) for fast domain adaptation in face recognition. |
