Deep Generative Adversarial Networks for Image-to-Image Translation: A Review
Many image processing, computer graphics, and computer vision problems can be treated as image-to-image translation tasks. Such translation entails learning to map one visual representation of a given input to another representation. Image-to-image translation with generative adversarial networks (G...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-10-01
|
| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/12/10/1705 |
| _version_ | 1797550780824158208 |
|---|---|
| author | Aziz Alotaibi |
| author_facet | Aziz Alotaibi |
| author_sort | Aziz Alotaibi |
| collection | DOAJ |
| description | Many image processing, computer graphics, and computer vision problems can be treated as image-to-image translation tasks. Such translation entails learning to map one visual representation of a given input to another representation. Image-to-image translation with generative adversarial networks (GANs) has been intensively studied and applied to various tasks, such as multimodal image-to-image translation, super-resolution translation, object transfiguration-related translation, etc. However, image-to-image translation techniques suffer from some problems, such as mode collapse, instability, and a lack of diversity. This article provides a comprehensive overview of image-to-image translation based on GAN algorithms and its variants. It also discusses and analyzes current state-of-the-art image-to-image translation techniques that are based on multimodal and multidomain representations. Finally, open issues and future research directions utilizing reinforcement learning and three-dimensional (3D) modal translation are summarized and discussed. |
| first_indexed | 2024-03-10T15:34:20Z |
| format | Article |
| id | doaj.art-3b9a138ec5e846d2a943197cd56b7e8a |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-10T15:34:20Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-3b9a138ec5e846d2a943197cd56b7e8a2023-11-20T17:21:17ZengMDPI AGSymmetry2073-89942020-10-011210170510.3390/sym12101705Deep Generative Adversarial Networks for Image-to-Image Translation: A ReviewAziz Alotaibi0College of Computers and Information Technology, Taif University, Taif 21974, Saudi ArabiaMany image processing, computer graphics, and computer vision problems can be treated as image-to-image translation tasks. Such translation entails learning to map one visual representation of a given input to another representation. Image-to-image translation with generative adversarial networks (GANs) has been intensively studied and applied to various tasks, such as multimodal image-to-image translation, super-resolution translation, object transfiguration-related translation, etc. However, image-to-image translation techniques suffer from some problems, such as mode collapse, instability, and a lack of diversity. This article provides a comprehensive overview of image-to-image translation based on GAN algorithms and its variants. It also discusses and analyzes current state-of-the-art image-to-image translation techniques that are based on multimodal and multidomain representations. Finally, open issues and future research directions utilizing reinforcement learning and three-dimensional (3D) modal translation are summarized and discussed.https://www.mdpi.com/2073-8994/12/10/1705image-to-image translationgenerative adversarial networksadversarial learningdeep generative modeldeep learning |
| spellingShingle | Aziz Alotaibi Deep Generative Adversarial Networks for Image-to-Image Translation: A Review Symmetry image-to-image translation generative adversarial networks adversarial learning deep generative model deep learning |
| title | Deep Generative Adversarial Networks for Image-to-Image Translation: A Review |
| title_full | Deep Generative Adversarial Networks for Image-to-Image Translation: A Review |
| title_fullStr | Deep Generative Adversarial Networks for Image-to-Image Translation: A Review |
| title_full_unstemmed | Deep Generative Adversarial Networks for Image-to-Image Translation: A Review |
| title_short | Deep Generative Adversarial Networks for Image-to-Image Translation: A Review |
| title_sort | deep generative adversarial networks for image to image translation a review |
| topic | image-to-image translation generative adversarial networks adversarial learning deep generative model deep learning |
| url | https://www.mdpi.com/2073-8994/12/10/1705 |
| work_keys_str_mv | AT azizalotaibi deepgenerativeadversarialnetworksforimagetoimagetranslationareview |