The techniques for 3D indoor scene capturing are widely used, but the meshes
produced leave much to be desired. In this paper, we propose "RoomDreamer",
which leverages powerful natural language to synthesize a new room with a
different style. Unlike existing image synthesis methods, our work addresses
the challenge of synthesizing both geometry and texture aligned to the input
scene structure and prompt simultaneously. The key insight is that a scene
should be treated as a whole, taking into account both scene texture and
geometry. The proposed framework consists of two significant components:
Geometry Guided Diffusion and Mesh Optimization. Geometry Guided Diffusion for
3D Scene guarantees the consistency of the scene style by applying the 2D prior
to the entire scene simultaneously. Mesh Optimization improves the geometry and
texture jointly and eliminates the artifacts in the scanned scene. To validate
the proposed method, real indoor scenes scanned with smartphones are used for
extensive experiments, through which the effectiveness of our method is
demonstrated.

本文提出了基于自然语言的房间风格合成算法 RoomDreamer，通过 Geometry Guided Diffusion 和 Mesh Optimization 处理实现 3D 室内场景生成，大幅提升了几何和纹理的一致性和图像质量。

RoomDreamer: 基于文本驱动的连贯几何纹理室内场景 3D 合成

RoomDreamer: Text-Driven 3D Indoor Scene Synthesis with Coherent  Geometry and Texture

We propose a new tetrahedral meshing method, fTetWild, to convert triangle
soups into high-quality tetrahedral meshes. Our method builds on the TetWild
algorithm, replacing the rational triangle insertion with a new incremental
approach to construct and optimize the output mesh, interleaving triangle
insertion and mesh optimization. Our approach makes it possible to maintain a
valid floating-point tetrahedral mesh at all algorithmic stages, eliminating
the need for costly constructions with rational numbers used by TetWild, while
maintaining full robustness and similar output quality. This allows us to
improve on TetWild in two ways. First, our algorithm is significantly faster,
with running time comparable to less robust Delaunay-based tetrahedralization
algorithms. Second, our algorithm is guaranteed to produce a valid tetrahedral
mesh with floating-point vertex coordinates, while TetWild produces a valid
mesh with rational coordinates which is not guaranteed to be valid after
floating-point conversion. As a trade-off, our algorithm no longer guarantees
that all input triangles are present in the output mesh, but in practice, as
confirmed by our tests on the Thingi10k dataset, the algorithm always succeeds
in inserting all input triangles.

提出一种新的四面体网格方法，fTetWild，用于将三角形面片转换为高质量的四面体网格，该方法通过增量方法构建和优化输出网格，并交替进行三角形插入和网格优化。