Neural Volume Rendering: NeRF And Beyond

Abstract

Besides the COVID-19 pandemic and political upheaval in the US, 2020 was also the year in which neural volume rendering exploded onto the scene, triggered by the impressive NeRF paper by Mildenhall et al. (2020). Both of us have tried to capture this excitement, Frank on a blog post (Dellaert, 2020) and Yen-Chen in a Github collection (Yen-Chen, 2020). This note is an annotated bibliography of the relevant papers, and we posted the associated bibtex file on the repository.

Blog: https://dellaert.github.io/NeRF/ Bibtex: https://github.com/yenchenlin/awesome-NeRF

References in corpus (9)

• NeRF++: Analyzing and Improving Neural Radiance Fields
• Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance
• Neural Reflectance Fields for Appearance Acquisition
• Object-Centric Neural Scene Rendering
• pixelNeRF: Neural Radiance Fields from One or Few Images
• Portrait Neural Radiance Fields from a Single Image
• Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes
• Learned Initializations for Optimizing Coordinate-Based Neural Representations
• Neural Radiance Flow for 4D View Synthesis and Video Processing

Cited by in corpus (5)

• DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks
• Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey
• ShaRF: Shape-conditioned Radiance Fields from a Single View
• Volume Rendering of Neural Implicit Surfaces
• VaxNeRF: Revisiting the Classic for Voxel-Accelerated Neural Radiance Field