We propose the extremal transport (ET) which is a mathematical formalization of the theoretically best possible unpaired translation between a pair of domains w.r.t. the given similarity function. Inspired by the recent advances in neural optimal transport (OT), we propose a scalable algorithm to approximate ET maps as a limit of partial OT maps. We test our algorithm on toy examples and on the unpaired image-to-image translation task.

翻译：我们提出极值传输（ET）方法，这是对给定相似函数下两个域之间理论上最优非配对翻译的数学形式化。受神经最优传输（OT）领域最新进展的启发，我们提出一种可扩展算法，通过将ET映射逼近为部分OT映射的极限。我们在玩具示例及非配对图像到图像翻译任务上对算法进行了验证。