Logo design is a complex process for designers and color plays a very important role in logo design. The automatic colorization of logo sketch is of great value and full of challenges. In this paper, we propose a new logo design method based on Conditional Generative Adversarial Networks, which can output multiple colorful logos only by providing one logo sketch. We improve the traditional U-Net structure, adding channel attention and spatial attention in the process of skip-connection. In addition, the generator consists of parallel attention-based U-Net blocks, which can output multiple logo images. During the model optimization process, a style loss function is proposed to improve the color diversity of the logos. We evaluate our method on the self-built edges2logos dataset and the public edges2shoes dataset. Experimental results show that our method can generate more colorful and realistic logo images based on simple sketches. Compared to the classic networks, the logos generated by our network are also superior in visual effects.
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机译:Logo设计是设计师和颜色在徽标设计中起着非常重要的作用。 Logo Sketch的自动彩色具有很大的价值和充满挑战。在本文中,我们提出了一种基于条件生成的对冲网络的新的徽标设计方法,只能通过提供一个徽标草图来输出多个彩色徽标。我们改善了传统的U-Net结构,在跳过连接过程中增加了通道关注和空间关注。此外,发电机由并行关注的U-Net块组成,可以输出多个徽标图像。在模型优化过程中,提出了一种改善徽标的色彩分集的样式损失功能。我们在自建立的Edge2Logos数据集和公共Edges2shoes数据集中评估我们的方法。实验结果表明,我们的方法可以基于简单的草图产生更丰富多彩和现实的徽标图像。与经典网络相比,我们的网络生成的徽标在视觉效果中也是优越的。
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