Multimodal Unsupervised Image To Image

Multimodal unsupervised image-to-image translation is a task in the field of computer vision that aims to generate multiple translation results of an image from one domain into another domain using a single input image. This task achieves diverse image content transformation by learning the mapping relationship between different modalities without paired data, and it has a wide range of application values, such as image style transfer and cross-domain image generation.