SketchyDepth:从场景草图到RGB-D图像

G. Berardi, Samuele Salti, L. D. Stefano
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引用次数: 0

摘要

基于草图的内容生成是一种创造性和有趣的活动,适合休闲和专业用户,有许多不同的应用程序。今天,可以通过绘制草图来生成单个物体的几何形状和外观。然而,只有外观可以从整个场景的草图合成。在本文中,我们提出了第一种从草图生成整个场景的深度图和图像的方法。我们演示了如何从双重角度生成几何信息作为深度图是有益的。一方面提高了由草图合成的图像的质量;另一方面,它解锁了深度支持的创意效果,如散景,雾,光线变化,3D照片和许多其他,这有助于以可控的方式增强最终输出。我们验证了我们的方法,展示了如何直接从草图生成深度图,相对于其他方法,即在图像生成后运行MiDaS,产生更好的定性结果。最后,我们介绍了深度素描,这是一种深度操作技术,可以在不需要额外注释或训练的情况下进一步条件图像生成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SketchyDepth: from Scene Sketches to RGB-D Images
Sketch-based content generation is a creative and fun activity suited to casual and professional users that has many different applications. Today it is possible to generate the geometry and appearance of a single object by sketching it. Yet, only the appearance can be synthesized from a sketch of a whole scene. In this paper we propose the first method to generate both the depth map and image of a whole scene from a sketch. We demonstrate how generating geometrical information as a depth map is beneficial from a twofold perspective. On one hand, it improves the quality of the image synthesized from the sketch. On the other, it unlocks depth-enabled creative effects like Bokeh, fog, light variation, 3D photos and many others, which help enhancing the final output in a controlled way. We validate our method showing how generating depth maps directly from sketches produces better qualitative results with respect to alternative methods, i.e. running MiDaS after image generation. Finally we introduce depth sketching, a depth manipulation technique to further condition image generation without the need of additional annotation or training.
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