We proposed an unsupervised image-to-image translation method by employing a bidirectional style transfer network with a cyclic collaborative loss to train the ...

In this paper, we propose a bidirectional style transfer method by exchanging the style of inputs while preserv- ing the structural information.

We proposed an unsupervised image-to-image translation method by employing a bidirectional style transfer network with a cyclic collaborative loss to train the ...

This paper describes a semantic transfer approach called MinT (Minimal Transfer) that has been developed in the speech-to-speech MT system verbmobil.

Abstract. Unsupervised image-to-image translation intends to learn a mapping of an image in a given domain to an analogous image in a different domain, without ...

Missing: Bidirectional Style Transfer.

Mar 24, 2022 · We propose an unsupervised image-to-image translation model with a compact structure called Re-EnGAN. Firstly, encoders on the same image domain can be reused.

Unsupervised image-to-image translation aims to learn the translation between two visual domains without paired data. Despite the recent progress in image ...

Enables the image-to-image translation without image labeling process. Achieves comparable performance to the cutting-edge supervised method.

Nov 30, 2022 · This paper focuses on researching and testing the U-GAT-IT unsupervised image style transfer method.