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WaveFill: A Wavelet-based Generation Network for Image Inpainting
[article]
2021
arXiv
pre-print
Image inpainting aims to complete the missing or corrupted regions of images with realistic contents. The prevalent approaches adopt a hybrid objective of reconstruction and perceptual quality by using generative adversarial networks. However, the reconstruction loss and adversarial loss focus on synthesizing contents of different frequencies and simply applying them together often leads to inter-frequency conflicts and compromised inpainting. This paper presents WaveFill, a wavelet-based
arXiv:2107.11027v1
fatcat:sf6s4vehvfakti5brjgspc5gb4