LTM-NeRF:在 HDR 神经辐射场中嵌入 3D 局部色调映射。

Xin Huang, Qi Zhang, Ying Feng, Hongdong Li, Qing Wang
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引用次数: 0

摘要

神经辐射场(NeRF)的最新进展为新型视图合成提供了一种新的几何原型。高动态范围 NeRF(HDR NeRF)能以更高的动态范围呈现新颖的视图。然而,在动态范围有限的各种设备上有效显示 HDR NeRF 的场景内容是一项重大挑战。为了解决这个问题,我们提出了 LTM-NeRF,一种旨在恢复 HDR NeRF 并支持 3D 局部色调映射的方法。LTM-NeRF 允许在不同曝光设置下合成 HDR 视图、色调映射视图和 LDR 视图,仅使用多视图多曝光 LDR 输入进行监督。具体来说,我们提出了一个用于 HDR NeRF 重建的可变相机响应函数(CRF)模块,可将场景的 HDR 辐射度全局映射到 LDR 像素。此外,我们还引入了神经曝光场(NeEF)来表示 HDR NeRF 的空间变化曝光时间,以实现三维局部色调映射,从而兼容各种显示器。综合实验证明,我们的方法不仅能准确合成 HDR 视图和曝光变化的 LDR 视图,还能自然渲染局部色调映射视图。有关视频结果,请查看我们的补充材料或访问项目页面:https://xhuangcv.github.io/LTM-NeRF/。
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LTM-NeRF: Embedding 3D Local Tone Mapping in HDR Neural Radiance Field.

Recent advances in Neural Radiance Fields (NeRF) have provided a new geometric primitive for novel view synthesis. High Dynamic Range NeRF (HDR NeRF) can render novel views with a higher dynamic range. However, effectively displaying the scene contents of HDR NeRF on diverse devices with limited dynamic range poses a significant challenge. To address this, we present LTM-NeRF, a method designed to recover HDR NeRF and support 3D local tone mapping. LTM-NeRF allows for the synthesis of HDR views, tone-mapped views, and LDR views under different exposure settings, using only the multi-view multi-exposure LDR inputs for supervision. Specifically, we propose a differentiable Camera Response Function (CRF) module for HDR NeRF reconstruction, globally mapping the scene's HDR radiance to LDR pixels. Moreover, we introduce a Neural Exposure Field (NeEF) to represent the spatially varying exposure time of an HDR NeRF to achieve 3D local tone mapping, for compatibility with various displays. Comprehensive experiments demonstrate that our method can not only synthesize HDR views and exposure-varying LDR views accurately but also render locally tone-mapped views naturally. For video results, please view our supplemental materials or visit the project page at: https://xhuangcv.github.io/LTM-NeRF/.

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