论文标题
跨光谱神经辐射场
Cross-Spectral Neural Radiance Fields
论文作者
论文摘要
我们提出了X-NERF，这是一种基于神经辐射场公式，从具有不同光谱灵敏度的相机捕获的跨光谱场景表示的新方法，给出了X-NERF。 X-NERF在训练过程中优化了整个光谱的相机姿势，并利用归一化的跨设备坐标（NXDC）从任意观点来渲染不同模态的图像，这些观点是对齐的，并以相同的分辨率对齐。在16个面向前面的场景上进行的实验，具有颜色，多光谱和红外图像，证实了X-NERF在建模跨光谱场景表示方面的有效性。
We propose X-NeRF, a novel method to learn a Cross-Spectral scene representation given images captured from cameras with different light spectrum sensitivity, based on the Neural Radiance Fields formulation. X-NeRF optimizes camera poses across spectra during training and exploits Normalized Cross-Device Coordinates (NXDC) to render images of different modalities from arbitrary viewpoints, which are aligned and at the same resolution. Experiments on 16 forward-facing scenes, featuring color, multi-spectral and infrared images, confirm the effectiveness of X-NeRF at modeling Cross-Spectral scene representations.
