Boundless: Generative Adversarial Networks for Image Extension [article]

Piotr Teterwak, Aaron Sarna, Dilip Krishnan, Aaron Maschinot, David Belanger, Ce Liu, William T. Freeman
2019 arXiv   pre-print
Image extension models have broad applications in image editing, computational photography and computer graphics. While image inpainting has been extensively studied in the literature, it is challenging to directly apply the state-of-the-art inpainting methods to image extension as they tend to generate blurry or repetitive pixels with inconsistent semantics. We introduce semantic conditioning to the discriminator of a generative adversarial network (GAN), and achieve strong results on image
more » ... ension with coherent semantics and visually pleasing colors and textures. We also show promising results in extreme extensions, such as panorama generation.
arXiv:1908.07007v1 fatcat:fv3a2j6bprcffm5cibtsoicxam