论文标题
为图像生成和编辑建模艺术工作流程
Modeling Artistic Workflows for Image Generation and Editing
论文作者
论文摘要
人们经常遵循涉及多个阶段的艺术工作流程来创造艺术，从而为整体设计提供了信息。如果艺术家希望修改较早的决定，则可能需要大量工作才能将这一新决定传播到最终艺术品。在上述观察中，我们提出了一个生成模型，该模型遵循给定的艺术工作流程，从而使多阶段的图像生成以及现有艺术品的多阶段图像编辑。此外，对于编辑方案，我们引入了一个优化过程以及基于学习的正则化，以确保模型与最初提供的图像紧密相位的编辑图像。三个不同艺术数据集的定性和定量结果证明了拟议框架对图像生成和编辑任务的有效性。
People often create art by following an artistic workflow involving multiple stages that inform the overall design. If an artist wishes to modify an earlier decision, significant work may be required to propagate this new decision forward to the final artwork. Motivated by the above observations, we propose a generative model that follows a given artistic workflow, enabling both multi-stage image generation as well as multi-stage image editing of an existing piece of art. Furthermore, for the editing scenario, we introduce an optimization process along with learning-based regularization to ensure the edited image produced by the model closely aligns with the originally provided image. Qualitative and quantitative results on three different artistic datasets demonstrate the effectiveness of the proposed framework on both image generation and editing tasks.
