mlsanityData to 14 Oct 2026

Progressive Multi-scale Light Field Networks

arXiv 2208.06710 ↗First posted 13 Aug 2022cs.CV cs.GRcited by 3

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Abstract (arXiv)

Neural representations have shown great promise in their ability to represent radiance and light fields while being very compact compared to the image set representation. However, current representations are not well suited for streaming as decoding can only be done at a single level of detail and requires downloading the entire neural network model. Furthermore, high-resolution light field networks can exhibit flickering and aliasing as neural networks are sampled without appropriate filtering. To resolve these issues, we present a progressive multi-scale light field network that encodes a light field with multiple levels of detail. Lower levels of detail are encoded using fewer neural network weights enabling progressive streaming and reducing rendering time. Our progressive multi-scale light field network addresses aliasing by encoding smaller anti-aliased representations at its lower levels of detail. Additionally, per-pixel level of detail enables our representation to support dithered transitions and foveated rendering.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 48 of its 74 references that are in the map. First posted on arXiv 13 Aug 2022.

Builds on

48 of 74 references.

References · 48

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36 more
  1. 2021FastNeRF: High-Fidelity Neural Rendering at 200FPScited by 511
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  13. 2021BungeeNeRF: Progressive Neural Radiance Field for Extreme Multi-scale Scene Renderingcited by 229
  14. 2020FastBERT: a Self-distilling BERT with Adaptive Inference Timecited by 226
  15. 2021HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fieldscited by 214
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  18. 2020Real-Time High-Resolution Background Mattingcited by 173
  19. 2022Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-timecited by 165
  20. 2017Adaptive Neural Networks for Efficient Inferencecited by 163
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  24. 2021Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representationscited by 82
  25. 2020MatryODShka: Real-time 6DoF Video View Synthesis using Multi-Sphere Imagescited by 64
  26. 2021CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fieldscited by 55
  27. 2021Neural Point Light Fieldscited by 51
  28. 2021FiG-NeRF: Figure-Ground Neural Radiance Fields for 3D Object Category Modellingcited by 47
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  36. 2021Light Field Implicit Representation for Flexible Resolution Reconstructioncited by 3

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Cited by year

Citing papers per year: 2023: 1; 2024: 1; 2025: 1.

3 papers.

  1. 2025Sketch and Patch: Efficient 3D Gaussian Representation for Man-Made Scenescited by 20
  2. 2023Continuous Levels of Detail for Light Field Networkscited by 1
  3. 2024LapisGS: Layered Progressive 3D Gaussian Splatting for Adaptive Streamingcited by 0