13 citations · 16 across the 3 of their papers we have counts for
4 papers
PCAAE: Principal Component Analysis Autoencoder for organising the latent space of generative networks
Chi-Hieu Pham, Saïd Ladjal, Alasdair Newson
Autoencoders and generative models produce some of the most spectacular deep learning results to date. However, understanding and controlling the latent space of these models prese…
High Resolution Face Age Editing
Xu Yao, Gilles Puy, Alasdair Newson +2
Face age editing has become a crucial task in film post-production, and is also becoming popular for general purpose photography. Recently, adversarial training has produced some o…
Processsing Simple Geometric Attributes with Autoencoders
Alasdair Newson, Andrés Almansa, Yann Gousseau +1
Image synthesis is a core problem in modern deep learning, and many recent architectures such as autoencoders and Generative Adversarial networks produce spectacular results on hig…
A PCA-like Autoencoder
Saïd Ladjal, Alasdair Newson, Chi-Hieu Pham
An autoencoder is a neural network which data projects to and from a lower dimensional latent space, where this data is easier to understand and model. The autoencoder consists of…