Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly- Throughs

Carnegie Mellon University

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Abstract

We use neural radiance fields (NeRFs) to build interac-tive 3D environments from large-scale visual captures spanning buildings or even multiple city blocks collected pri-marily from drones. In contrast to single object scenes (on which NeRFs are traditionally evaluated), our scale poses multiple challenges including (1) the need to model thou-sands of images with varying lighting conditions, each of which capture only a small subset of the scene, (2) pro-hibitively large model capacities that make it infeasible to train on a single GPU, and (3) significant challenges for fast rendering that would enable interactive fly-throughs. To address these challenges, we begin by analyzing visi-bility statistics for…

Citation impact

368
total citations
FWCI
28.33
Percentile
100%
References
59
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • Rendering (computer graphics)
  • Speedup
  • Scalability
  • Exploit
  • Artificial intelligence
  • Segmentation
  • Computer vision
UN Sustainable Development Goals
  • Sustainable cities and communities
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