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头部艺术家-VL:视觉/语言引导的3D头部生成与自评分蒸

Hongyu Liu, Xuan Wang, Ziyu Wan

IEEE transactions on pattern analysis and machine intelligence

|October 10, 2025

概括

HeadArtist-VL使用自评分蒸 (SSD) 从视觉或语言输入生成高质量的3D头部. 这种方法显著优于现有的3D头部生成和编辑技术.

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:

从各种输入中生成现实的3D头部模型仍然是一个挑战.
现有的方法往往在处理视觉和文本指导方面缺乏灵活性.
控制精细细节的生成过程对于应用至关重要.

研究的目的:

介绍HeadArtist-VL,这是一个高效的3D头部生成和编辑管道.
以参考图像或语言提示为指导的3D头部合成.
为了实现可控制的几何形状和外观的高保真3D头部模型.

主要方法:

使用地标导向的ControlNet作为优化3D头部模型的生成优先级.
采用自评分蒸 (SSD) 进行高效的管道优化.
集成视觉和语言输入通过一种基于扩散的新方法,包括图像编码器和新视图合成.

主要成果:

HeadArtist-VL生产高质量的3D头部雕塑,具有丰富的几何形状和光现实的外观.
该方法显著优于3D头部生成的最先进方法.
证明成功的编辑操作,包括几何变形和外观修改.

结论:

HeadArtist-VL为3D头部生成和编辑提供了一种多功能和有效的解决方案.
拟议的自评分蒸 (SSD) 框架允许在视觉/语言指导下进行强大的优化.
该方法显示出强大的潜力,用于需要现实的和可编辑的3D头部模型的应用.

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