Problem
Research questions and friction points this paper is trying to address.
geometric stylization
3D mesh deformation
image-guided
style transfer
3D generation
Image-Guided Geometric Stylization of 3D Meshes
🤖 AI Summary
Existing generative models struggle to achieve large-scale geometric deformations guided by images while preserving both the 3D mesh topology and part-level semantic structure. To address this challenge, this work proposes an image-driven framework for 3D mesh geometric stylization. The method leverages a pretrained diffusion model to extract abstract geometric representations from target images, combines differentiable rendering with an approximate VAE encoder to provide stable gradients, and employs a coarse-to-fine multi-scale deformation strategy to enable diverse style transfer. This approach is the first to effectively maintain original topological and semantic integrity under significant geometric deformation, successfully generating stylized 3D meshes that faithfully reflect the pose and contour characteristics of the input images, thereby substantially enhancing the expressiveness of artistic 3D content creation.
📝 Abstract
Recent generative models can create visually plausible 3D representations of objects. However, the generation process often allows for implicit control signals, such as contextual descriptions, and rarely supports bold geometric distortions beyond existing data distributions. We propose a geometric stylization framework that deforms a 3D mesh, allowing it to express the style of an image. While style is inherently ambiguous, we utilize pre-trained diffusion models to extract an abstract representation of the provided image. Our coarse-to-fine stylization pipeline can drastically deform the input 3D model to express a diverse range of geometric variations while retaining the valid topology of the original mesh and part-level semantics. We also propose an approximate VAE encoder that provides efficient and reliable gradients from mesh renderings. Extensive experiments demonstrate that our method can create stylized 3D meshes that reflect unique geometric features of the pictured assets, such as expressive poses and silhouettes, thereby supporting the creation of distinctive artistic 3D creations. Project page: https://changwoonchoi.github.io/GeoStyle
Innovation
Methods, ideas, or system contributions that make the work stand out.
geometric stylization
3D mesh deformation
diffusion models
coarse-to-fine pipeline
VAE encoder
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