梦之石:图像作为文本引导的3D形状生成的基石
IEEE transactions on pattern analysis and machine intelligence
|October 2, 2023
概括
梦石从文本中生成3D形状,没有配对数据,使用图像作为中间步骤. 这种方法提高了3D形状生成质量和文本的一致性.
科学领域:
- 计算机视觉 计算机视觉
- 计算机图形 计算机图形
- 人工智能的人工智能
背景情况:
- 从文本描述生成3D形状是具有挑战性的,因为缺乏大规模的配对文本-3D数据集.
- 现有的方法经常在文本提示和生成的3D模型之间的忠实性和一致性方面扎.
研究的目的:
- 介绍DreamStone,一种新的以文本为导向的3D形状生成方法.
- 通过利用中间图像表示来实现3D形状生成而不需要配对的文本-3D数据.
- 为了增强生成的3D形状的多样性,真实性和造型能力.
主要方法:
- 一个两阶段的特征空间对齐策略,使用预训练的单视图重建 (SVR) 模型.
- 将CLIP图像特征映射到SVR模型的3D形状空间.
- 将CLIP文本特征映射到3D形状空间,通过CLIP与染图像的一致性.
- 集成一个以文本为导向的3D形状造型模块.
- 利用预先训练的文本到图像扩散模型进行增强生成.
主要成果:
- 梦石成功地从文本描述中生成3D形状,而没有配对数据.
- 与最先进的方法相比,这种方法显示出优越的生成质量和一致性.
- 造型模块以新的结构和纹理增强生成的形状.
- 与扩散模型的整合提高了生成多样性和忠诚度.
结论:
- 梦石提供了一种灵活可扩展的解决方案,用于以文本为导向的3D形状生成.
- 该方法有效地弥合了文本和3D形状模式之间的差距.
- 该方法显示了在3D内容创建和AI研究中的各种应用的巨大潜力.
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