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- W2890970519 abstract "Endowing user-specified emotions on arbitrary images will be an interesting application. The emotion transfer of landscape photograph has shown greater appeal than the emotion transfer of facial image in the field of art design or painting. In this work, we present a novel method to synthesize arbitrarily specified emotions into the inputted landscape images. With style transfer aiming to generate the style of the source image while preserving the content of the target image, an Image Emotionalizing Network is developed for emotional rendering based on style transfer by using convolutional neural networks. Other than the feed-forward transfer networks which may be limited to single emotion transfer, an extension version of instance normalization is adopted to make our method suitable for the transfer of multiple emotions. As the datasets that we conduct are sufficient to train a well-performing network, our experimental results demonstrate that the proposed method can synthesize impressive emotional images and the experimental speed is equivalent to the previous effective methods." @default.
- W2890970519 created "2018-09-27" @default.
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- W2890970519 date "2018-01-01" @default.
- W2890970519 modified "2023-09-27" @default.
- W2890970519 title "Arbitrary Image Emotionalizing with Style Transfer" @default.
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- W2890970519 doi "https://doi.org/10.1007/978-3-030-00764-5_37" @default.
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