论文标题
生成对象邮票
Generating Object Stamps
论文作者
论文摘要
我们提出了一种算法，以生成各种前景对象，并使用GAN体系结构将它们复合到背景图像中。给定一个对象类，一个用户提供的边界框和背景图像，我们首先使用掩码生成器创建对象形状，然后使用纹理生成器填充掩码，使纹理与背景集成在一起。通过将对象插入的问题分开到这两个阶段中，我们表明我们的模型使我们能够改善不同对象生成的现实主义，这也与所提供的背景图像一致。与最先进的对象插入方法相比，我们对具有挑战性的可可数据集的结果表明，总体质量和多样性提高了。
We present an algorithm to generate diverse foreground objects and composite them into background images using a GAN architecture. Given an object class, a user-provided bounding box, and a background image, we first use a mask generator to create an object shape, and then use a texture generator to fill the mask such that the texture integrates with the background. By separating the problem of object insertion into these two stages, we show that our model allows us to improve the realism of diverse object generation that also agrees with the provided background image. Our results on the challenging COCO dataset show improved overall quality and diversity compared to state-of-the-art object insertion approaches.
