Colorizing Monochromatic Radiance Fields

• URL: http://arxiv.org/abs/2402.12184v1
• Date: Mon, 19 Feb 2024 14:47:23 GMT
• Title: Colorizing Monochromatic Radiance Fields
• Authors: Yean Cheng, Renjie Wan, Shuchen Weng, Chengxuan Zhu, Yakun Chang, Boxin Shi
• Abstract summary: We consider reproducing color from monochromatic radiance fields 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.
• Score: 55.695149357101755
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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