#papers with code

Paper with Code Series: Adversarial Latent Autoencoders

Generative Adversarial Networks continues to be one of the main deep learning techniques in current computer vision with machine learning developments. But they have been shown to have some issues regarding the quality of images it outputs from a generator’s map input space. This may have some causal explanation with the way GANs process of encoding-decoding from a known probability distribution…

Recently I have found some interesting papers and analysis about the issue of semantic synthesis and segmentation used both for natural language processing and for advanced computer vision imaging. I tended to be skeptical of this use of the word ‘semantic’, but then I realized that within the field of computer science, the term is related with a formal treatment of how programming languages…