AI 中文总结
针对神经渲染在2D设备上查看限制感知真实感问题，提出基于多平面图像的波光学渲染管道，该算法在运行时大幅超越现有算法，速度提升显著，且图像质量优，经多数据集验证性能出色。
AI 中文摘要
神经渲染的最新进展在3D重建和新视图合成方面带来了前所未有的能力，但这些渲染在电脑屏幕或传统VR头显上以2D图像形式查看，限制了感知真实感和沉浸感。新的3D场景表示的快速发展需要将现有3D内容转换为与新兴3D显示技术兼容的格式的专用渲染算法。本文提出一种与多平面图像（MPI）配合使用的波光学渲染管道，用于高效和高质量的全息图合成。基于MPI的计算机生成全息算法在运行时大大优于基于原始图形的CGH算法，速度提升高达250,000倍，同时在图像质量上显著优于传统的基于层的CGH算法。我们在各种3D场景数据集上进行了广泛验证，展示了出色的3D焦栈和4D光场重建性能且不牺牲效率。
英文摘要
Recent advances in neural rendering have unlocked unprecedented capabilities in 3D reconstruction and novel view synthesis, giving rise to applications such as virtual fly-throughs of a 3D scene reconstructed from a set of sparse, casually captured images. However, these renderings are viewed on a computer screen or conventional VR headsets as 2D images, greatly limiting the perceptual realism and immersiveness of such experiences. The rapid development in novel 3D scene representations calls for dedicated rendering algorithms that convert these readily-available 3D contents into formats that are compatible with emerging 3D display technologies, such as holographic displays. In this paper, we propose a wave-optics rendering pipeline that works with multiplane images (MPIs) for efficient and high-quality hologram synthesis. Our MPI-based computer-generated holography algorithm greatly outperforms state-of-the-art primitive-based CGH algorithms in terms of runtime, achieving speedups up to 250,000x while achieving comparable image quality, and significantly outperforms conventional layer-based CGH algorithms in terms of image quality. We validate our method extensively on a wide variety of 3D scene datasets both in simulation and through experimentally captured results, showing exceptional 3D focal stack and 4D light field reconstruction performance without sacrificing efficiency.
