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- W4383748749 abstract "The paper presents a structure-preserving domain adaptation network, termed SDANet. To address the problem of edge blurring or incompleteness in the pencil sketches generated by existing methods, we designed a structure-preserving module to extract the edges of both the real-world photos and the generated real-world photos, then constrained them with a structure-preserving loss, in order to produce clearer edges in the generated pencil sketches. In addition, we constructed a real-world photo and pencil sketch dataset for training the pencil sketches generation network, named RW-PS, which comprises an extensive collection of high-quality pencil sketches. Experimental results demonstrate that our method generates pencil sketches with a lowest FID score compared to existing SOTA methods on the RW-PS dataset. Moreover, in user surveys, the pencil sketches generated by our proposed method received the highest number of votes." @default.
- W4383748749 created "2023-07-11" @default.
- W4383748749 creator A5066444166 @default.
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- W4383748749 date "2023-05-12" @default.
- W4383748749 modified "2023-10-09" @default.
- W4383748749 title "Structure-preserving Domain Adaptation Network for Generating Pencil Sketches" @default.
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- W4383748749 doi "https://doi.org/10.1109/cvidl58838.2023.10166910" @default.
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