An image inpainting method based on the high-efficiency transformer

Jiaqi Yang; Xuesong Su

doi:10.1117/12.3035428

19 July 2024 An image inpainting method based on the high-efficiency transformer

Jiaqi Yang, Xuesong Su

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 1321307 (2024) https://doi.org/10.1117/12.3035428
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

In this paper, we introduce an image restoration network that is based on the High-Efficiency Transformer (HET). The model utilizes fast Fourier convolution for image enhancement, incorporates self-attention mechanisms for capturing contextual information, and employs convolution for feature extraction and classification. Additionally, we improve the network's performance and convergence speed by implementing batch normalization and residual concatenation. Experimental results show substantial enhancements in image restoration achieved through our deep learning-based approach. The reconstructed images demonstrate improved clarity, enhanced details, and reduced dependence on manual interventions.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiaqi Yang and Xuesong Su "An image inpainting method based on the high-efficiency transformer", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 1321307 (19 July 2024); https://doi.org/10.1117/12.3035428

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