Though Neural Radiance Fields (NeRF) can produce colorful 3D representations of the world by using a set of 2D images, such ability becomes non-existent when only monochromatic images are provided. Since color is necessary in representing the world, reproducing color from monochromatic radiance fields becomes crucial. To achieve this goal, instead of manipulating the monochromatic radiance fields directly, we consider it as a representation-prediction task in the Lab color space. By first constructing the luminance and density representation using monochromatic images, our prediction stage can recreate color representation on the basis of an image colorization module. We then reproduce a colorful implicit model through the representation of luminance, density, and color. Extensive experiments have been conducted to validate the effectiveness of our approaches. Our project page: https://liquidammonia.github.io/color-nerf.

翻译：虽然神经辐射场（NeRF）可以通过一组二维图像生成世界的彩色三维表示，但当仅提供单色图像时，这种能力将不复存在。由于色彩对表征世界至关重要，从单色辐射场中再现色彩变得关键。为实现这一目标，我们并未直接操控单色辐射场，而是将其视为Lab色彩空间中的表示-预测任务。首先利用单色图像构建亮度和密度表示，预测阶段可基于图像彩色化模块重建色彩表示。随后通过亮度、密度和色彩的表示共同生成彩色隐式模型。大量实验验证了本方法有效性。项目页面：https://liquidammonia.github.io/color-nerf。