GASP：用于基于物理模拟的高斯泼溅
GASP: Gaussian Splatting for Physic-Based Simulations
AI总结：
提出GASP流水线，通过参数化扁平高斯分布将物理引擎建模简化为3D点处理，结合高斯分组策略实现高效模拟，在3D对象渲染基准上表现卓越。
摘要：
物理模拟对于在各种现实世界应用中建模和利用3D场景至关重要。然而，将其与最先进的3D场景渲染技术（如Gaussian Splatting，GS）集成仍然具有挑战性。现有模型使用额外的网格化机制，包括三角形或四面体网格化、移动立方体或笼状网格。或者，我们可以修改基于物理的牛顿动力学以与3D高斯分量对齐。当前模型采用变形图的一阶近似，通过线性变换局部近似动力学。相比之下，我们的基于物理模拟的GS（GASP）流水线使用参数化的扁平高斯分布。因此，使用物理引擎建模高斯分量的问题被简化为处理3D点。在我们的工作中，我们提出了操纵高斯分布的额外规则，演示了如何调整流水线以结合网格、在模拟过程中控制高斯大小并提高模拟效率。这是通过高斯分组策略实现的，该策略实现了分层结构，并使模拟可以仅在选定的高斯分布上执行。由此产生的解决方案可以集成到任何可视为黑盒的物理引擎中。如我们的研究所证明，所提出的流水线在为3D对象渲染设计的各种基准数据集上表现出卓越的性能。包含额外可视化的项目网页可在https://waczjoan.github.io/GASP找到。
英文摘要：
Physics simulation is paramount for modeling and utilizing 3D scenes in various real-world applications. However, integrating with state-of-the-art 3D scene rendering techniques such as Gaussian Splatting (GS) remains challenging. Existing models use additional meshing mechanisms, including triangle or tetrahedron meshing, marching cubes, or cage meshes. Alternatively, we can modify the physics-grounded Newtonian dynamics to align with 3D Gaussian components. Current models take the first-order approximation of a deformation map, which locally approximates the dynamics by linear transformations. In contrast, our GS for Physics-Based Simulations (GASP) pipeline uses parametrized flat Gaussian distributions. Consequently, the problem of modeling Gaussian components using the physics engine is reduced to working with 3D points. In our work, we present additional rules for manipulating Gaussians, demonstrating how to adapt the pipeline to incorporate meshes, control Gaussian sizes during simulations, and enhance simulation efficiency. This is achieved through the Gaussian grouping strategy, which implements hierarchical structuring and enables simulations to be performed exclusively on selected Gaussians. The resulting solution can be integrated into any physics engine that can be treated as a black box. As demonstrated in our studies, the proposed pipeline exhibits superior performance on a diverse range of benchmark datasets designed for 3D object rendering. The project webpage, which includes additional visualizations, can be found at https://waczjoan.github.io/GASP.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
