Feature Splatting: Language-Driven Physics-Based Scene Synthesis and Editing
원문 초록
Scene representations using 3D Gaussian primitives have produced excellent results in modeling the appearance of static and dynamic 3D scenes. Many graphics applications, however, demand the ability to manipulate both the appearance and the physical properties of objects. We introduce Feature Splatting, an approach that unifies physics-based dynamic scene synthesis with rich semantics from vision language foundation models that are grounded by natural language. Our first contribution is a way to distill high-quality, object-centric vision-language features into 3D Gaussians, that enables semi-automatic scene decomposition using text queries. Our second contribution is a way to synthesize physics-based dynamics from an otherwise static scene using a particle-based simulator, in which material properties are assigned automatically via text queries. We ablate key techniques used in this pipeline, to illustrate the challenge and opportunities in using feature-carrying 3D Gaussians as a unified format for appearance, geometry, material properties and semantics grounded on natural language. Project website: https://feature-splatting.github.io/
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
M3: 3D-Spatial MultiModal Memory
PFGS: High Fidelity Point Cloud Rendering via Feature Splatting
Feature Splatting for Better Novel View Synthesis with Low Overlap
Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis
OpenSplat3D: Open-Vocabulary 3D Instance Segmentation using Gaussian Splatting
ReasonGrounder: LVLM-Guided Hierarchical Feature Splatting for Open-Vocabulary 3D Visual Grounding and Reasoning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.