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Augmented Cyclic Consistency Regularization for Unpaired Image-To-Image Translation
- Source :
- ICPR
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- Unpaired image-to-image (I2I) translation has received considerable attention in pattern recognition and computer vision because of recent advancements in generative adversarial networks (GANs). However, due to the lack of explicit supervision, unpaired I2I models often fail to generate realistic images, especially in challenging datasets with different backgrounds and poses. Hence, stabilization is indispensable for GANs and applications of I2I translation. Herein, we propose Augmented Cyclic Consistency Regularization (ACCR), a novel regularization method for unpaired I2I translation. Our main idea is to enforce consistency regularization originating from semi-supervised learning on the discriminators leveraging real, fake, reconstructed, and augmented samples. We regularize the discriminators to output similar predictions when fed pairs of original and perturbed images. We qualitatively clarify why consistency regularization on fake and reconstructed samples works well. Quantitatively, our method outperforms the consistency regularized GAN (CR-GAN) in real-world translations and demonstrates efficacy against several data augmentation variants and cycle-consistent constraints.<br />Comment: Accepted to ICPR2020
- Subjects :
- FOS: Computer and information sciences
Computer Science - Machine Learning
Computer science
business.industry
Computer Vision and Pattern Recognition (cs.CV)
Computer Science - Computer Vision and Pattern Recognition
Pattern recognition
02 engineering and technology
Iterative reconstruction
010501 environmental sciences
Translation (geometry)
01 natural sciences
Regularization (mathematics)
Image (mathematics)
Machine Learning (cs.LG)
Consistency (statistics)
Pattern recognition (psychology)
0202 electrical engineering, electronic engineering, information engineering
Image translation
020201 artificial intelligence & image processing
Artificial intelligence
business
0105 earth and related environmental sciences
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Proceedings of ICPR 2020 25th International Conference on Pattern Recognition
- Accession number :
- edsair.doi.dedup.....c174cfd93fbf62e94aaf35a5bbb78675