P‐2.1: Multi‐Scale Feature Fusion Generative Adversarial Network for Image Inpainting

Existing image inpainting networks may cause distorted image structures and blurred textures during restoration. Therefore, we propose an image inpainting algorithm based on Multi‐Scale Feature Fusion Generative Adversarial Network (MSFF). First, we use a Context Fusion Transformer Block (CFTB) to enlarge the receptive field of the defective image and reduce the feature loss caused by sampling. Second, we design an Aperture Attention Block (ATAB) to capture the shallow feature information and perform fine‐grained feature fusion. Finally, through the decoder, we generate high‐quality inpainted images step by step from coarse to fine. The results of multiple experiments show that our method has a better inpainting effect.