Edge-enhanced GAN with Vanishing Points for Image Inpainting
Kei Masaoka, Irawati Nurmala Sari, Weiwei Du · 2022
Reconstructing the damaged images with perspective views has an extensive range in the field of image inpainting. However, most existing methods generated inadequately realistic restored images. Accomplishing this problem, we propose an edge-enhanced image generation model considering viewpoints. Our method applies edge map information to guide image generation based on the perspective views of an image using vanishing points detection. Texture synthesis will be presented as post-processing to complete the remaining missing regions. Experiment shows that our approach can generate perspective images with convincing details, such as indoor and outdoor facades.