Anycost GAN is a type of generative adversarial network for image synthesis and editing. Given an input image, we project it into the latent space with encoder $E$ and backward optimization. We can modify the latent code with user input to edit the image. During editing, a sub-generator of small cost is used for fast and interactive preview; during idle time, the full cost generator renders the final, high-quality output. The outputs from the full and sub-generators are visually consistent during projection and editing.
Source: Anycost GANs for Interactive Image Synthesis and EditingPaper | Code | Results | Date | Stars |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |