HVTR++:图像和姿势驱动的人类化身使用混合体积度-纹理染
IEEE transactions on visualization and computer graphics
|July 21, 2023
概括
混合体积度-纹理染 (HVTR++) 通过姿势和视图图像合成高质量的3D人类化身. 这种新的方法有效地从复杂的动作中生成详细的化身,改进了现有的神经染技术.
科学领域:
- 计算机视觉 计算机视觉
- 计算机图形 计算机图形
- 机器学习 机器学习
背景情况:
- 神经染方法擅长于摄影现实的人类化身生成.
- 由于身体姿势等有限的驾驶信号,现有的方法难以提供详细的外观.
- 低维信号无法捕捉到全身人类外表的复杂性.
研究的目的:
- 开发一种新的神经染管道,用于合成高质量的3D人类化身.
- 通过整合驾驶视图图像来提高头像细节的真实性.
- 为了从任意的姿势和观点中实现高效和高质量的化身合成.
主要方法:
- 拟议的混合体体积测量纹理染 (HVTR++) 管道.
- 学习的姿势和视图图像信号在一个密集的紫外线分流器上的紫外线对齐的特征.
- 使用姿势和图像条件的神经辐射场 (PID-NeRF) 构建了一个3D体积表示.
- 在图像空间中融合了体积特征与2D纹理特征.
- 采用基于生成对抗网络 (GAN) 的快速纹理染器进行高分辨率输出.
主要成果:
- HVTR++成功地从任意的姿势和视图中合成了详细的3D人形.
- 混合染方法有效地处理复杂的运动和自我封闭.
- 通过高质量的化身生成,实现了高效的推断时间.
- 与现有方法相比,证明了最先进的定量结果.
结论:
- HVTR++为3D人类化身合成提供了一种高效和高质量的解决方案.
- 积分和纹理染的整合克服了以前方法的局限性.
- 管道有效地保留了外观细节,并处理复杂的动态.
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