arXiv:2411.06067
AI-Driven Stylization of 3D Environments
원문 초록
In this system, we discuss methods to stylize a scene of 3D primitive objects into a higher fidelity 3D scene using novel 3D representations like NeRFs and 3D Gaussian Splatting. Our approach leverages existing image stylization systems and image-to-3D generative models to create a pipeline that iteratively stylizes and composites 3D objects into scenes. We show our results on adding generated objects into a scene and discuss limitations.
함께 살펴볼 논문
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PhysX: Physical-Grounded 3D Asset Generation
OmniConsistency: Learning Style-Agnostic Consistency from Paired Stylization Data
SOAP: Style-Omniscient Animatable Portraits
SVAD: From Single Image to 3D Avatar via Synthetic Data Generation with Video Diffusion and Data Augmentation
DiMeR: Disentangled Mesh Reconstruction Model
Objaverse++: Curated 3D Object Dataset with Quality Annotations
토론
이 논문과 연결된 포럼 글이 아직 없습니다.