Narrative Goldmine

Scene Capture and Reconstruction

5 min read

Properties

Type
  • Note
Status
  • stable
Generated
  • by: process:vault-migrate/1.0 · at: 2026-09-22T12:41:58.55607396Z

NeRFs

  • Early Foundations of NeRF:
    • Early Photography and Photosculpture (ca 1850): Pioneers in photography began experimenting with aerial photogrammetry and photosculptures, creating 3D representations from multiple 2D photographs, laying groundwork for future 3D capture technologies.
  • Plenoptic Function and Light Fields (1908 & 1936):
    • Gabriel Lippmann introduces the concept of the plenoptic function which evolves into the light field concept, simplifying the capture and representation of light as it travels through space.
  • Advances in Computing and Graphics (1960-1980s):
    • The development of lasers, holograms, and computer graphics sets the stage for more advanced 3D representations and the capture of light fields.
  • Lightfield Camera Arrays and Image-Based Rendering (2000):
    • The introduction of lightfield camera arrays and image-based rendering techniques brings light fields into practical use, although it remains complex and niche.
  • Generative AI and Inverse Rendering Birth of NeRF (2020):
    • Neural Radiance Fields (NeRF): A breakthrough in 2020 with the introduction of NeRF, offering an efficient way to recreate 3D scenes from 2D images using neural networks.
  • Realtime NeRF and Commercial Applications (2022):
    • NVIDIA’s Instant-NGP: Accelerates NeRF processing, enabling real-time rendering on consumer-grade hardware and facilitating wider adoption and practical applications in various fields.
  • The Future of NeRF:
    • The continuous development of NeRF is expected to integrate more seamlessly with web browsers, game engines, and potentially transform large-scale mapping, video conferencing, and real-time interactive applications.

LIDAR

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