Abstract
We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other 3D representations like voxels and point clouds, meshes are more desirable in practice, because (1) they enable easy and arbitrary manipulation of shapes for relighting and simulation, and (2) they can fully leverage the power of modern graphics pipelines which are mostly optimized for meshes. Previous scalable methods for generating meshes typically rely on sub-optimal post-processing, and they tend to produce overly-smooth or noisy surfaces without fine-grained geometric details. To overcome these shortcomings, we take advantage of the graph structure of meshes and use a simple yet very effective generative modeling method to generate 3D meshes. Specifically, we represent meshes with deformable tetrahedral grids, and then train a diffusion model on this direct parametrization. We demonstrate the effectiveness of our model on multiple generative tasks.
Abstract (translated)
我们考虑生成逼真的三维形状,这对许多应用如自动场景生成和物理模拟等非常有用。与其他三维表示方法如立方晶格和点云相比,网格在实践中更受欢迎,因为(1)它们能够方便和任意地操纵形状进行照明和模拟,(2)它们能够充分利用现代图形管道的高效性,这些管道主要优化于网格。以前的可扩展生成网格方法通常依赖于次优的后期处理,它们往往产生过于平滑或噪声丰富的表面,缺乏精细的几何细节。为了克服这些缺点,我们利用网格的图结构,并使用一个简单的但非常有效的生成建模方法生成三维网格。具体来说,我们使用可变形的四元组网格表示网格,然后训练一个扩散模型在这个直接参数化上。我们证明了我们模型在多个生成任务中的 effectiveness。
URL
https://arxiv.org/abs/2303.08133
