INODE is trained like a standard RNN, it learns to discriminate short event sequences and to perform event-by-event online inference.
This paper introduces a neural style transfer model to generate a stylized image conditioning on a set of examples describing the desired style.
We then compare the daytime and translated night images to obtain a pose estimate for the night image using the known 6-DOF position of the closest day image.
This year alone has seen unprecedented leaps in the area of learning-based image translation, namely CycleGAN, by Zhu et al.
Ranked #6 on Facial Expression Translation on CelebA