3DStyleGLIP：面向部件定制的文本引导3D神经风格化
3DStyleGLIP: Part-Tailored Text-Guided 3D Neural Stylization
AI总结：
针对现有3D风格化方法仅支持整体风格化、缺乏细粒度可控性的问题，提出3DStyleGLIP框架，利用GLIP的视觉-语言嵌入空间实现文本引导的部件级3D风格化，提升3D内容创作的定制灵活性。
摘要：
3D风格化指为三维对象赋予特定风格，可生成适配多样场景的独特风格3D对象，具备巨大商业潜力。近期人工智能与文本驱动操控方法的进展，让风格化流程愈发直观且自动化。这类方法通过降低对人工劳动与专业技能的依赖削减了人力成本，但它们主要聚焦整体风格化，忽略了为3D对象的单个部件施加目标风格的能力，这一局限限制了细粒度可控性。为填补这一空白，我们提出3DStyleGLIP，这是一款专为文本驱动的部件定制3D风格化设计的新型框架。给定一个3D网格与一条文本提示词，3DStyleGLIP利用Grounding Language-Image Pre-training（GLIP，接地语言-图像预训练）模型的视觉-语言嵌入空间，定位3D网格的各个部件，并修改其外观以匹配文本提示词中指定的风格。3DStyleGLIP借助部件级风格损失与两种互补学习技术，通过端到端流程在GLIP的共享嵌入空间中有效整合了部件定位与风格化引导。该神经方法满足了用户的细粒度风格编辑需求，能生成高质量的部件专属风格化结果，为3D内容创作的定制化与灵活性开辟了新可能。我们的代码与结果可在https://github.com/sj978/3DStyleGLIP获取。
英文摘要：
3D stylization, the application of specific styles to three-dimensional objects, offers substantial commercial potential by enabling the creation of uniquely styled 3D objects tailored to diverse scenes. Recent advancements in artificial intelligence and text-driven manipulation methods have made the stylization process increasingly intuitive and automated. While these methods reduce human costs by minimizing reliance on manual labor and expertise, they predominantly focus on holistic stylization, neglecting the application of desired styles to individual components of a 3D object. This limitation restricts the fine-grained controllability. To address this gap, we introduce 3DStyleGLIP, a novel framework specifically designed for text-driven, part-tailored 3D stylization. Given a 3D mesh and a text prompt, 3DStyleGLIP utilizes the vision-language embedding space of the Grounded Language-Image Pre-training (GLIP) model to localize individual parts of the 3D mesh and modify their appearance to match the styles specified in the text prompt. 3DStyleGLIP effectively integrates part localization and stylization guidance within GLIP's shared embedding space through an end-to-end process, enabled by part-level style loss and two complementary learning techniques. This neural methodology meets the user's need for fine-grained style editing and delivers high-quality part-specific stylization results, opening new possibilities for customization and flexibility in 3D content creation. Our code and results are available at https://github.com/sj978/3DStyleGLIP.
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。
