GAN inversion aims to invert a given image back into the latent space of a pretrained GAN model, for the image to be faithfully reconstructed from the inverted code by the generator. As an emerging technique to bridge the real and fake image domains, GAN inversion plays an essential role in enabling the pretrained GAN models such as StyleGAN and BigGAN to be used for real image editing applications. Meanwhile, GAN inversion also provides insights on the interpretation of GAN's latent space and how the realistic images can be generated. In this paper, we provide an overview of GAN inversion with a focus on its recent algorithms and applications. We cover important techniques of GAN inversion and their applications to image restoration and image manipulation. We further elaborate on some trends and challenges for future directions.
翻译：GAN Inversion旨在将一个特定图像倒回一个经过预先训练的GAN模型的潜在空间,以便从发电机的倒置代码中忠实地重建该图像。作为连接真实和假图像域的一种新兴技术,GAN Inversion在使经过训练的GAN模型,如StyleGAN和BigGAN能够用于真实图像编辑应用程序方面发挥着至关重要的作用。与此同时,GAN Inversion还提供对GAN潜在空间的解释以及如何产生现实图像的见解。在本文中,我们提供了GAN的翻版概览,重点是其最近的算法和应用。我们涵盖了GAN的翻版重要技术及其用于图像恢复和图像操纵的应用。我们进一步阐述了未来方向的一些趋势和挑战。
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