The creation of photorealistic virtual worlds requires the accurate modeling
of 3D surface geometry for a wide range of objects. For this, meshes are
appealing since they 1) enable fast physics-based rendering with realistic
material and lighting, 2) support physical simulation, and 3) are
memory-efficient for modern graphics pipelines. Recent work on reconstructing
and statistically modeling 3D shape, however, has critiqued meshes as being
topologically inflexible. To capture a wide range of object shapes, any 3D
representation must be able to model solid, watertight, shapes as well as thin,
open, surfaces. Recent work has focused on the former, and methods for
reconstructing open surfaces do not support fast reconstruction with material
and lighting or unconditional generative modelling. Inspired by the observation
that open surfaces can be seen as islands floating on watertight surfaces, we
parameterize open surfaces by defining a manifold signed distance field on
watertight templates. With this parameterization, we further develop a
grid-based and differentiable representation that parameterizes both watertight
and non-watertight meshes of arbitrary topology. Our new representation, called
Ghost-on-the-Shell (G-Shell), enables two important applications:
differentiable rasterization-based reconstruction from multiview images and
generative modelling of non-watertight meshes. We empirically demonstrate that
G-Shell achieves state-of-the-art performance on non-watertight mesh
reconstruction and generation tasks, while also performing effectively for
watertight meshes.

创建逼真的虚拟世界需要对广泛对象的三维表面几何进行准确建模，我们提出了一种名为 G-Shell 的新表示方法，通过定义一个流形符号距离场在完全密封的模板上对开放表面进行参数化，实现了多视图图像重建和非完全密封网格的生成建模。