Resources on faces/poses generative network

[Clorr]

Found here https://github.com/nightrome/really-awesome-gan :

• A GAN that generates frontal faces from other poses. Maybe this can help if we lack some poses from target dataset. Maybe they could be generated.
• Pose Guided Person Image Generation. This network generates poses from landmarks. Also has some insterest for low detail generation

[shaoanlu]

Another relevant one:

GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data

• https://arxiv.org/abs/1705.04932
• https://www.youtube.com/watch?v=KUsVH7P-5vE
• https://github.com/Prinsphield/GeneGAN
• From the abstract: "Overall, our deterministic generative model learns disentangled attribute subspaces from weakly labeled data by adversarial training. Experiments on CelebA and Multi-PIE datasets validate the effectiveness of the proposed model on real world data, in generating images with specified eyeglasses, smiling, hair styles, and lighting conditions etc."