Day 176(Computer Vision) -- Age-Invariant Face Recognition

Feature Factorization -- A linear factorization module is introduced that decomposes the entire set of facial features into two sets of uncorrelated components(age & identity). This is followed by retrieving age-related details through a mapping function'R' and the residual part is considered as the identity component. During the inference time, only the identity-related features are utilised for face recognition. The first backbone network is similar to ResNets which extracts the initial features from the entire image. Decorrelated Adversarial Learning -- Even though we want both the components to be independent of each other, practically identity has some mix of features from the age information.