Data Structure ?
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Data Structure ?
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README.md
現在、GANに基づくアート生成方法は条件入力に依存するため、非独創的なアート作品を生成します。ここでは、条件入力なしで中国山水画を最初から最後まで生成する初のモデルであるSketch - And - Paint GAN（SAPGAN）を提案します。SAPGANは2つのGANで構成されています。SketchGANはエッジマップを生成するために使用され、PaintGANはその後のエッジから絵画への変換に使用されます。当社のモデルは、これまで生成研究に使用されたことのない新しい中国伝統山水画のデータセットで学習されました。242人を対象とした視覚的チューリングテスト研究によると、SAPGANによる絵画が人間のアート作品と誤認される頻度は55％で、ベースラインGANによる絵画を大きく上回っています。当社の研究は、真の機械独創的アート生成の基礎を築きます。
このデータセットを研究に使用する場合は、論文を引用してください。
@misc{xue2020endtoend,
タイトル={敵対的生成ネットワークを用いた中国山水画のエンドツーエンド創作},
著者={アリス・薛},
年={2020},
電子版={2011.05552},
アーカイブ接頭辞={arXiv},
主要分類={cs.CV}
}
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