Image inpainting aims to fill the missing hole of the input. It is hard to solve this task efficiently when facing the high-resolution images due to two reasons: (1) Large reception field needs to be handled for high-resolution image inpainting. (2) The general encoder and decoder network synthesize many background pixels synchronously due to the form of image matrix. In this paper, we try to break the above limitations for the first time thanks to the recent development of continuous implicit representation. In detail, we down-sample and encode the degraded image to produce the spatial-adaptive parameters for each spatial patch via an attentional Fast Fourier Convolution~(FFC)-based parameter generation network. Then, we take these parameters as the weights and biases of a series of multi-layer perceptrons~(MLPs), where the input is the encoded continuous coordinates and the output is the synthesized color value. Thanks to the proposed structure, we only encode the high-resolution image in a relatively low resolution for larger reception fields capturing, and then, the continuous position encoding will be helpful to synthesize the photo-realistic high-frequency textures by re-sampling the coordinate in the higher resolution. Also, our framework enables us to query the coordinates of missing pixels only in parallel, yielding a more efficient solution than the previous methods. Experiments show that the proposed method achieves the real-time performance on the 2048X2048 images using a single GTX 2080 Ti GPU and can handle 4096X4096 images, with much better performance than existing state-of-the-art methods visually and numerically. The code and models will be made available.

CoordFill: Efficient High-Resolution Image Inpainting via Parameterized Coordinate Querying

CV: Computational Photography, Image & Video Synthesis 1

poster

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AAAI 2023

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines.

Weihuang Liu

1

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CoordFill: Efficient High-Resolution Image Inpainting via Parameterized Coordinate Querying

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