Learning image-to-image translation using paired and unpaired training samples

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Summary

This work proposes a new general purpose image-to-image translation model that is able to utilize both paired and unpaired training data simultaneously, and is the first work to consider such hybrid setup in image- to- image translation.

Type
preprint
Published
2018-05-08
Cited by
46
References
40
Access
Open access

Keywords

Image translation, Image (mathematics), Translation (biology), Computer science, Artificial intelligence

References

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