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Grayscale Image Colorization with GAN and CycleGAN in Different Image Domain

2024-01-21 · Chen Liang, Yunchen Sheng, Yichen Mo

Automatic colorization of grayscale image has been a challenging task. Previous research have applied supervised methods in conquering this problem [ 1]. In this paper, we reproduces a GAN-based coloring model, and experiments one of its variant. We also proposed a CycleGAN based model and experiments those methods on various datasets. The result shows that the proposed CycleGAN model does well in human-face coloring and comic coloring, but lack the ability to diverse colorization.

📄 PDF Abstract BibTeX arXiv:2401.11425

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ColorizationImage Colorization

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Residual Connection 설명 없음
Sigmoid Activation 설명 없음
Cycle Consistency Loss Cycle Consistency Loss is a type of loss used for generative adversarial networks that performs unpaired image-to-image translation. It was introduced with the…
Batch Normalization 설명 없음
Residual Block Residual Blocks are skip-connection blocks that learn residual functions with reference to the layer inputs, instead of learning unreferenced functions. They were introduced…
GAN Least Squares Loss GAN Least Squares Loss is a least squares loss function for generative adversarial networks. Minimizing this objective function is equivalent to minimizing the Pearson…

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