Exploring double cross cyclic interpolation in unpaired image-to-image translation

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Lopez J.
Mauricio A.
Camara G.
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Institute of Electrical and Electronics Engineers Inc.
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The unpaired image-to-image translation consists of transferring a sample a in the domain A to an analog sample b in the domain B without intensive pixel-to-pixel supervision. The current vision focuses on learning a generative function that maps both domains but ignoring the latent information, although its exploration is not explicit supervision. This paper proposes a cross-domain GAN-based model to achieve a bi-directional translation guided by latent space supervision. The proposed architecture provides a double-loop cyclic reconstruction loss in an exchangeable training adopted to reduce mode collapse and enhance local details. Our proposal has outstanding results in visual quality, stability, and pixel-level segmentation metrics over different public datasets.
Palabras clave
Unpaired Image to Image Translation, Cross domain interpolation, Latent space exploration