Abstract
How can we edit or transform the geometric or color property of a point cloud? In this study, we propose a neural style transfer method for point clouds which allows us to transfer the style of geometry or color from one point cloud either independently or simultaneously to another. This transfer is achieved by manipulating the content representations and Gram-based style representations extracted from a pre-trained PointNet-based classification network for colored point clouds. As Gram-based style representation is invariant to the number or the order of points, the same method can be extended to transfer the style extracted from an image to the color expression of a point cloud by merely treating the image as a set of pixels. Experimental results demonstrate the capability of the proposed method for transferring style from either an image or a point cloud to another point cloud of a single object or even an indoor scene.
Abstract (translated)
如何编辑或转换点云的几何或颜色属性？在这项研究中，我们提出了一种点云的神经风格转移方法，它允许我们将几何或颜色的风格从一个点云独立地或同时转移到另一个点云。这种转换是通过操作从预先训练的基于点网的彩色点云分类网络中提取的内容表示和基于gram的样式表示来实现的。由于基于gram的样式表示对点的数量或顺序是不变的，因此可以扩展相同的方法，仅将图像视为一组像素，将从图像中提取的样式传输到点云的颜色表达式。实验结果表明，该方法能够将图像或点云的风格转换为单个物体甚至室内场景的另一点云。
URL
https://arxiv.org/abs/1903.05807
