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HCC: Small: 3DStylus: User-Guided Shape Manipulation using Neural Priors

HCC：小型：3DStylus：使用神经先验进行用户引导的形状操作

基本信息

批准号：
2304481
负责人：
Rana Hanocka
金额：
$ 59.99万
依托单位：
University of Chicago
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2023
资助国家：
美国
起止时间：
2023-04-01 至 2026-03-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2304481&HistoricalAwards=false
关键词：
HCC Small 3DStylus User Guided

项目摘要

Digital 3D models are used in a wide variety of applications, including manufacturing, engineering, medicine, and entertainment. The rapid growth in demand for 3D models, however, has outpaced our ability to construct them. Employing current modeling tools to perform even the most basic of 3D operations, such as selecting a region on a shape, requires years of extensive training and experience. This project will develop new and accessible tools and techniques for creating and manipulating 3D objects, eliminating existing technical barriers of entry and thereby democratizing 3D content creation. Project outcomes will have broad impact by making 3D modeling more accessible, empowering both expert and lay users to create and transform objects for applications across a wide range of industries and professions. The project is centered around the development of 3DStylus, a suite of foundational tools that will enable users to edit and modify existing 3D shapes and create new ones from scratch, using simple text as input. 3D Stylus will encompass three central components: (i) 3D Editor, which will enhance existing 3D models by incorporating text-specified textures, materials, and localized modifications that preserve the underlying shape; (ii) 3D Morpher, which will transform existing 3D models into new text-specified geometry, while preserving the original texture details; and (iii) 3D Creator, which will allow users to intuitively create novel 3D geometries, and make desired edits and manipulations, using only a text description. The research will leverage deep learning techniques which have been used so successfully in 2D (as evidenced by the revolutionary impact of DALL-E), but which have generally been out-of-reach in 3D given the relatively small amount of available high-quality 3D data. The novel approaches envisioned will instead use the abundantly available 2D datasets as a signal for editing 3D objects. Thus, the transformational potential of deep learning can be harnessed to achieve advanced 3D modeling capabilities, without the need for large 3D datasets.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

数字3D模型用于各种各样的应用，包括制造、工程、医学和娱乐。然而，对3D模型需求的快速增长已经超过了我们构建它们的能力。使用当前的建模工具来执行最基本的3D操作，例如选择形状上的区域，需要多年的广泛培训和经验。该项目将开发新的和可访问的工具和技术，用于创建和操作3D对象，消除现有的技术障碍，从而使3D内容创作民主化。项目成果将产生广泛的影响，使3D建模更容易访问，使专家和非专业用户能够为广泛的行业和专业的应用程序创建和转换对象。该项目围绕3DStylus的开发，这是一套基础工具，使用户能够编辑和修改现有的3D形状，并使用简单的文本作为输入从头开始创建新的形状。3D Stylus将包括三个核心部分：㈠ 3D编辑器，它将通过纳入文本指定的纹理、材料和保留基本形状的局部修改来增强现有的3D模型; ㈡ 3D变形器，它将把现有的3D模型转换成新的文本指定的几何形状，同时保留原始纹理细节;以及（iii）3D Creator，这将允许用户仅使用文本描述直观地创建新颖的3D几何形状，并进行所需的编辑和操作。该研究将利用深度学习技术，这些技术在2D中已经成功使用（DALL-E的革命性影响就是证明），但由于可用的高质量3D数据相对较少，这些技术在3D中通常是遥不可及的。设想的新方法将使用大量可用的2D数据集作为编辑3D对象的信号。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响力审查标准进行评估，被认为值得支持。