Artist-Net: Decorating the Inferred Content With Unified Style for Image Inpainting
Recently, context learning networks have shown promise in filling large holes in natural images. These networks can decorate the predicted contents with high-frequency details by borrowing or copying neural information from the known region. However, this operation might introduce undesired content...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/d2d758844a1b48b6a09a7d4b1ef2b6a2 |
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