Abstract
Image-to-image translation (I2I) transforms an image from a source domain to a target domain while preserving source content. Most computer vision applications are in the field of image-to-image translation, such as style transfer, image segmentation, and photo enhancement. The degree of preservation of the content of the source images in the translation process can be different according to the problem and the intended application. From this point of view, in this paper, we divide the different tasks in the field of image-to-image translation into three categories: Fully Content preserving, Partially Content preserving, and Non-Content preserving. We present different tasks, datasets, methods, results of methods for these three categories in this paper. We make a categorization for I2I methods based on the architecture of different models and study each category separately. In addition, we introduce well-known evaluation criteria in the I2I translation field. Specifically, nearly 70 different I2I models were analyzed, and more than 10 quantitative evaluation metrics and 30 distinct tasks and datasets relevant to the I2I translation problem were both introduced and assessed. Translating from simulation to real images could be well viewed as an application of fully content preserving or partially content preserving unsupervised image-to-image translation methods. So, we provide a benchmark for Sim-to-Real translation, which can be used to evaluate different methods. In general, we conclude that because of the different extent of the obligation to preserving content in various applications, it is better to consider this issue in choosing a suitable I2I model for a specific application.
Abstract (translated)
图像到图像翻译（I2I）是指将一个领域中的图像转换为另一个领域的图像，同时保留源图的内容。大多数计算机视觉应用都属于图像到图像翻译的范畴，例如风格迁移、图像分割和照片增强等。在翻译过程中，根据问题类型及应用场景的不同，保留源图内容的程度也会有所差异。从这个角度来看，在本文中我们将不同任务分为三类：完全保留内容（Fully Content Preserving）、部分保留内容（Partially Content Preserving）以及不保留内容（Non-Content Preserving）。在这篇文章中，我们介绍了这三种类别下的不同任务、数据集、方法及其相应的方法结果。基于模型的不同架构，我们对I2I方法进行了分类，并单独研究了每个类别。此外，还介绍了一些在图像到图像翻译领域内广为认可的评估标准。具体来说，本文分析了近70种不同的I2I模型，并介绍了超过10项定量评估指标及30个与I2I翻译问题相关的不同任务和数据集。 从模拟图像向真实图像转换可以视作完全保留内容或部分保留内容的无监督图像到图像翻译方法的应用。因此，我们提供了Sim-to-Real（仿真到现实）翻译的一个基准测试平台，可用于评估不同的方法。总的来说，我们认为由于各种应用在保留内容方面的义务程度不同，选择适用于特定应用场景的I2I模型时应该考虑这个问题。
URL
https://arxiv.org/abs/2502.08667
