Image synthesis at CVPR 2020 | Generative blog

This year the conference was hosted in a virtual format. It greatly reduced the number of networking for me, but allowed paying attention to more papers. Regarding the drawbacks, I listed them separately here https://twitter.com/digitman_/status/1274612391523860480 During the conference, I took notes and decided to share them. No notes were taken on the papers that I had studied in great detail earlier. That is why articles like StyleGAN2 and StarGAN2 were not included in the list. For this post to be appropriate, it will only be about image generation (well, almost). Cross-Domain Correspondence Learning for Exemplar-Based Image TranslationGeneration of images by the segmentation mask using an example image. Style during generation is just taken from the example. In fact, it also allows you to edit arbitrary images, if there is a segmentation for them. Pipeline: by the picture of the segmentation map and picture example they extract features with different encoders into the same latent

2 mentions: @digitman_@twt05
Keywords: cvpr
Date: 2020/06/29 00:00

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