论文标题
Paint2Pix：基于交互式绘画的渐进图像合成和编辑
Paint2Pix: Interactive Painting based Progressive Image Synthesis and Editing
论文作者
论文摘要
用用户涂抹的可控图像合成是对计算机视觉社区感兴趣的主题。在本文中，我们首次研究了不完整和原始人类绘画的影像现实主义图像综合问题。特别是，我们提出了一种新颖的方法Paint2Pix，该方法通过学习从不完整的人类绘画的多种映射到其现实效果图的映射，可以从基本的笔触输入中预测（和适应）“用户想要绘制的内容”。当与自动绘画剂的最新作品结合使用时，我们表明Paint2Pix可用于从头开始进行渐进的图像合成。在此过程中，Paint2Pix允许新手用户逐步合成所需的图像输出，同时只需要几乎没有粗的用户涂鸦来准确地引导合成过程的轨迹。此外，我们发现我们的方法还构成了一种令人惊讶的方便方法，可以进行真实的图像编辑，并允许用户通过仅添加几种位置良好的笔触来执行各种自定义细粒度编辑。补充视频和演示可从https://1jsingh.github.io/paint2pix获得
Controllable image synthesis with user scribbles is a topic of keen interest in the computer vision community. In this paper, for the first time we study the problem of photorealistic image synthesis from incomplete and primitive human paintings. In particular, we propose a novel approach paint2pix, which learns to predict (and adapt) "what a user wants to draw" from rudimentary brushstroke inputs, by learning a mapping from the manifold of incomplete human paintings to their realistic renderings. When used in conjunction with recent works in autonomous painting agents, we show that paint2pix can be used for progressive image synthesis from scratch. During this process, paint2pix allows a novice user to progressively synthesize the desired image output, while requiring just few coarse user scribbles to accurately steer the trajectory of the synthesis process. Furthermore, we find that our approach also forms a surprisingly convenient approach for real image editing, and allows the user to perform a diverse range of custom fine-grained edits through the addition of only a few well-placed brushstrokes. Supplemental video and demo are available at https://1jsingh.github.io/paint2pix
