Unraveling the Impact of Explainability of Artificial Intelligence-Generated Content(AIGC) on Design Style Transfer Effects-Reference-Cited by-同舟云学术

Unraveling the Impact of Explainability of Artificial Intelligence-Generated Content(AIGC) on Design Style Transfer Effects

Published:2023-12-14 Issue: Volume: Page:171-185
ISSN:
Container-title:Proceedings of the 2023 9th International Conference on Communication and Information Processing
language:
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Author:

Ren Zhilin¹^ORCID,Qin Xiangang²^ORCID,Wang Bixuan¹^ORCID

Affiliation:

1. School of Digital Media and Design Arts, Beijing University of Posts and Telecommunications, Beijing, China, China

2. School of Digital Media and Design Arts, Beijing University of Posts and Telecommunications, Beijing, China, China and Beijing Key Laboratory of Network System and Network Culture, Beijing University of Posts and Telecommunications, Beijing, China, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3638884.3638910

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4. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, AidanN. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is All you Need. Neural Information Processing Systems,Neural Information Processing Systems (June 2017).

5. Image Style Transfer Using Convolutional Neural Networks

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