Image Inpainting Method based on Multi-scale Feature Fusion
Xiaofeng Qiu, Youdong Ding, Bing Yu · 2021 IEEE 5th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) · 2021
To solve the problems of texture blurring and structure inconsistency in large area image inpainting. This paper proposes an image inpainting method based on multi-scale feature fusion. We design a multi-scale feature fusion module to expand the receptive field. Besides, we devise attention module to capture information from distant areas in the feature map. In this paper, partial convolution and recursive structure are adopted to repair the boundary of the missing area progressively. This method can continuously strengthen the constraint on the center of the missing region and make the repair results more refined. Experimental results show that, compared with the existing image inpainting methods, this structure improves the performance of image inpainting, and the image quality generated by it is the best.