Unpaired Image-to-Image Translation with Content Preserving Perspective: A Review

Fuente: arXiv
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Autores principales: Safayani, Mehran, Mirzapour, Behnaz, aghaebrahimiyan, Hanieh, Salehi, Nasrin, Ravaee, Hamid
Formato: Preprint
Publicado: 2025
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author Safayani, Mehran
Mirzapour, Behnaz
aghaebrahimiyan, Hanieh
Salehi, Nasrin
Ravaee, Hamid
author_facet Safayani, Mehran
Mirzapour, Behnaz
aghaebrahimiyan, Hanieh
Salehi, Nasrin
Ravaee, Hamid
contents 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.
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spellingShingle Unpaired Image-to-Image Translation with Content Preserving Perspective: A Review
Safayani, Mehran
Mirzapour, Behnaz
aghaebrahimiyan, Hanieh
Salehi, Nasrin
Ravaee, Hamid
Image and Video Processing
Computer Vision and Pattern Recognition
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.
title Unpaired Image-to-Image Translation with Content Preserving Perspective: A Review
topic Image and Video Processing
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2502.08667