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Deep Layer Aggregation Architectures for Photorealistic Universal Style Transfer
This paper introduces a deep learning approach to photorealistic universal style transfer that extends the PhotoNet network architecture by adding extra feature-aggregation modules. Given a pair of images representing the content and the reference of style, we augment the state-of-the-art solution m...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181698/ https://www.ncbi.nlm.nih.gov/pubmed/37177731 http://dx.doi.org/10.3390/s23094528 |