PiiGAN: Generative Adversarial Networks for Pluralistic Image Inpainting
The latest methods based on deep learning have achieved amazing results regarding the complex work of inpainting large missing areas in an image. But this type of method generally attempts to generate one single “optimal” result, ignoring many other plausible results. Consideri...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9027849/ |