Huang Xin, Zhang Qi, Feng Ying, Li Hongdong, Wang Qing
IEEE Trans Pattern Anal Mach Intell. 2024 Dec;46(12):10944-10959. doi: 10.1109/TPAMI.2024.3448620. Epub 2024 Nov 6.
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.
神经辐射场（NeRF）的最新进展为新视图合成提供了一种新的几何原语。高动态范围神经辐射场（HDR NeRF）能够以更高的动态范围渲染新视图。然而，在动态范围有限的各种设备上有效显示HDR NeRF的场景内容面临着重大挑战。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、色调映射视图和低动态范围（LDR）视图，仅使用多视图多曝光LDR输入进行监督。具体而言，我们为HDR NeRF重建提出了一个可微的相机响应函数（CRF）模块，将场景的HDR辐射全局映射到LDR像素。此外，我们引入了一个神经曝光场（NeEF）来表示HDR NeRF空间变化的曝光时间，以实现3D局部色调映射，从而与各种显示器兼容。综合实验表明，我们的方法不仅能够准确合成HDR视图和曝光变化的LDR视图，还能自然地渲染局部色调映射视图。
