mlsanityData to 14 Oct 2026

Complex-Valued Holographic Radiance Fields

arXiv 2506.08350 ↗First posted 10 Jun 2025cs.GR cs.CV cs.ETcited by 2

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Abstract (arXiv)

Modeling wave properties of light is an important milestone for advancing physically-based rendering. In this paper, we propose complex-valued holographic radiance fields, a method that optimizes scenes without relying on intensity-based intermediaries. By leveraging multi-view images, our method directly optimizes a scene representation using complex-valued Gaussian primitives representing amplitude and phase values aligned with the scene geometry. Our approach eliminates the need for computationally expensive holographic rendering that typically utilizes a single view of a given scene. This accelerates holographic rendering speed by 30x-10,000x while achieving on-par image quality with state-of-the-art holography methods, representing a promising step towards bridging the representation gap between modeling wave properties of light and 3D geometry of scenes.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 26 of its 64 references that are in the map. First posted on arXiv 10 Jun 2025.

Builds on

26 of 64 references.

References · 26

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  3. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  4. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 5,045
  5. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,964
  6. 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,076
  7. 2019Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelinescited by 672
  8. 2019Understanding Straight-Through Estimator in Training Activation Quantized Neural Netscited by 231
  9. 2020Free View Synthesiscited by 231
  10. 2024Taming 3DGS: High-Quality Radiance Fields with Limited Resourcescited by 204
  11. 2022Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Modelscited by 174
  12. 2020DeRF: Decomposed Radiance Fieldscited by 163
14 more
  1. 2024RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPScited by 113
  2. 2024GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splattingcited by 99
  3. 2023SMERF: Streamable Memory Efficient Radiance Fields for Real-Time Large-Scene Explorationcited by 62
  4. 2025FreeTimeGS: Free Gaussian Primitives at Anytime and Anywhere for Dynamic Scene Reconstructioncited by 54
  5. 20253D Scene Generation: A Surveycited by 24
  6. 2023Neural Spectro-polarimetric Fieldscited by 10
  7. 2023Multi-color Holograms Improve Brightness in Holographic Displayscited by 6
  8. 2024Holographic Parallax Improves 3D Perceptual Realismcited by 5
  9. 2022Pupil-aware Holographycited by 4
  10. 2025Gaussian Wave Splatting for Computer-Generated Holographycited by 4
  11. 2023Stochastic Light Field Holographycited by 3
  12. 2024Large 'Etendue 3D Holographic Display with Content-adaptive Dynamic Fourier Modulationcited by 3
  13. 2024Pupil-Adaptive 3D Holography Beyond Coherent Depth-of-Fieldcited by 2
  14. 2024Focal Surface Holographic Light Transport using Learned Spatially Adaptive Convolutionscited by 2

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Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025Complex-Valued 2D Gaussian Representation for Computer-Generated Holographycited by 0
  2. 2025A Large-Depth-Range Layer-Based Hologram Dataset for Machine Learning-Based 3D Computer-Generated Holographycited by 0