论文标题
文字到艺术形象生成
Text to artistic image generation
论文作者
论文摘要
绘画是人们表达自己想法的方式之一，但是如果手中的残疾人想要绘画怎么办？为了应对这一挑战，我们创建了一个端到端解决方案，可以从文本描述中生成艺术图像。但是，由于缺乏配对文本描述和艺术图像的数据集，因此很难直接训练可以根据文本输入创建艺术的算法。 To address this issue, we split our task into three steps: (1) Generate a realistic image from a text description by using Dynamic Memory Generative Adversarial Network (arXiv:1904.01310), (2) Classify the image as a genre that exists in the WikiArt dataset using Resnet (arXiv: 1512.03385), (3) Select a style that is compatible with the genre and transfer it to the generated image by使用神经艺术风格化网络（ARXIV：1705.06830）。
Painting is one of the ways for people to express their ideas, but what if people with disabilities in hands want to paint? To tackle this challenge, we create an end-to-end solution that can generate artistic images from text descriptions. However, due to the lack of datasets with paired text description and artistic images, it is hard to directly train an algorithm which can create art based on text input. To address this issue, we split our task into three steps: (1) Generate a realistic image from a text description by using Dynamic Memory Generative Adversarial Network (arXiv:1904.01310), (2) Classify the image as a genre that exists in the WikiArt dataset using Resnet (arXiv: 1512.03385), (3) Select a style that is compatible with the genre and transfer it to the generated image by using neural artistic stylization network (arXiv:1705.06830).
