Gaussian Splashing: Unified Particles for Versatile Motion Synthesis and Rendering
We demonstrate the feasibility of integrating physics-based animations of solids and fluids with 3D Gaussian Splatting (3DGS) to create novel effects in virtual scenes reconstructed using 3DGS. Leveraging the coherence of the Gaussian Splatting and Position-Based Dynamics (PBD) in the underlying representation, we manage rendering, view synthesis, and the dynamics of solids and fluids in a cohesive manner. Similar to GaussianShader, we enhance each Gaussian kernel with an added normal, aligning the kernel's orientation with the surface normal to refine the PBD simulation. This approach effectively eliminates spiky noises that arise from rotational deformation in solids. It also allows us to integrate physically based rendering to augment the dynamic surface reflections on fluids. Consequently, our framework is capable of realistically reproducing surface highlights on dynamic fluids and facilitating interactions between scene objects and fluids from new views. For more information, please visit our project page at \url{https://gaussiansplashing.github.io/}.
Code (0)
등록된 구현이 없습니다.
Tasks
3DGSMotion SynthesisSimilar Papers 제목 키워드 기반
Gaussian Splashing: Direct Volumetric Rendering Underwater
In underwater images, most useful features are occluded by water. The extent of the occlusion depends on imaging geometry and can vary even across a sequence of burst images. As a result, 3D reconstruction methods robust…
3DGS3D ReconstructionDepth EstimationImage features of a splashing drop on a solid surface extracted using a feedforward neural network
This article reports nonintuitive characteristic of a splashing drop on a solid surface discovered through extracting image features using a feedforward neural network (FNN). Ethanol of area-equivalent radius about 1.29 …
Correlation between morphological evolution of splashing drop and exerted impact force revealed by interpretation of explainable artificial intelligence
This study reveals a possible correlation between splashing morphology and the normalized impact force exerted by an impacting drop on a solid surface. This finding is obtained from a newly proposed feature extraction me…
ClassificationExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Features of a Splashing Drop on a Solid Surface and the Temporal Evolution extracted through Image-Sequence Classification using an Interpretable Feedforward Neural Network
This paper reports the features of a splashing drop on a solid surface and the temporal evolution, which are extracted through image-sequence classification using a highly interpretable feedforward neural network (FNN) w…
GenMatter: Perceiving Physical Objects with Generative Matter Models
Human visual perception offers valuable insights for understanding computational principles of motion-based scene interpretation. Humans robustly detect and segment moving entities that constitute independently moveable …
Object SegmentationScene Understanding