NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review

• URL: http://arxiv.org/abs/2210.00379v5
• Date: Thu, 30 Nov 2023 21:20:08 GMT
• Title: NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review
• Authors: Kyle Gao, Yina Gao, Hongjie He, Dening Lu, Linlin Xu and Jonathan Li
• Abstract summary: Neural Radiance Field (NeRF) has recently become a significant development in the field of Computer Vision. NeRF models have found diverse applications in robotics, urban mapping, autonomous navigation, virtual reality/augmented reality, and more.
• Score: 19.67372661944804
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Neural Radiance Field (NeRF) has recently become a significant development in the field of Computer Vision, allowing for implicit, neural network-based scene representation and novel view synthesis. NeRF models have found diverse applications in robotics, urban mapping, autonomous navigation, virtual reality/augmented reality, and more. Due to the growing popularity of NeRF and its expanding research area, we present a comprehensive survey of NeRF papers from the past two years. Our survey is organized into architecture and application-based taxonomies and provides an introduction to the theory of NeRF and its training via differentiable volume rendering. We also present a benchmark comparison of the performance and speed of key NeRF models. By creating this survey, we hope to introduce new researchers to NeRF, provide a helpful reference for influential works in this field, as well as motivate future research directions with our discussion section.

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