PD-GAN: Probabilistic Diverse GAN for Image Inpainting

Understand

We propose PD-GAN, a probabilistic diverse GAN for image inpainting.

• Given an input image with arbitrary hole regions, PD-GAN produces multiple inpainting results with diverse and visually realistic content.
• Our PD-GAN is built upon a vanilla GAN which generates images based on random noise.
• During image generation, we modulate deep features of input random noise from coarse-to-fine by injecting an initially restored image and the hole regions in multiple scales.