mlsanityData to 14 Oct 2026

A Real-time Method for Inserting Virtual Objects into Neural Radiance Fields

arXiv 2310.05837 ↗First posted 9 Oct 2023cs.CV cs.GRcited by 5

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Abstract (arXiv)

We present the first real-time method for inserting a rigid virtual object into a neural radiance field, which produces realistic lighting and shadowing effects, as well as allows interactive manipulation of the object. By exploiting the rich information about lighting and geometry in a NeRF, our method overcomes several challenges of object insertion in augmented reality. For lighting estimation, we produce accurate, robust and 3D spatially-varying incident lighting that combines the near-field lighting from NeRF and an environment lighting to account for sources not covered by the NeRF. For occlusion, we blend the rendered virtual object with the background scene using an opacity map integrated from the NeRF. For shadows, with a precomputed field of spherical signed distance field, we query the visibility term for any point around the virtual object, and cast soft, detailed shadows onto 3D surfaces. Compared with state-of-the-art techniques, our approach can insert virtual object into scenes with superior fidelity, and has a great potential to be further applied to augmented reality systems.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 34 of its 58 references that are in the map. First posted on arXiv 9 Oct 2023.

Builds on

34 of 58 references.

References · 34

  1. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  2. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  3. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,032
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  10. 2020NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesiscited by 496
  11. 2018Pyramid Stereo Matching Networkcited by 489
  12. 2020NeRD: Neural Reflectance Decomposition from Image Collectionscited by 449
22 more
  1. 2021Animatable Neural Radiance Fields for Modeling Dynamic Human Bodiescited by 361
  2. 2017End-to-End Learning of Geometry and Context for Deep Stereo Regressioncited by 360
  3. 2021PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relightingcited by 335
  4. 2021Learning Object-Compositional Neural Radiance Field for Editable Scene Renderingcited by 228
  5. 2019Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF from a Single Imagecited by 203
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  7. 2017MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstructioncited by 163
  8. 2017Learning to Predict Indoor Illumination from a Single Imagecited by 161
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  10. 2020Object-Centric Neural Scene Renderingcited by 90
  11. 2019Deep Parametric Indoor Lighting Estimationcited by 83
  12. 2021Learning Indoor Inverse Rendering with 3D Spatially-Varying Lightingcited by 83
  13. 2019Fast Spatially-Varying Indoor Lighting Estimationcited by 73
  14. 2019DeepLight: Learning Illumination for Unconstrained Mobile Mixed Realitycited by 63
  15. 2019Inverse Path Tracing for Joint Material and Lighting Estimationcited by 62
  16. 2018MVDepthNet: Real-time Multiview Depth Estimation Neural Networkcited by 59
  17. 2020EMLight: Lighting Estimation via Spherical Distribution Approximationcited by 48
  18. 2022Real-Time Neural Light Field on Mobile Devicescited by 48
  19. 2019Automatic Scene Inference for 3D Object Compositingcited by 36
  20. 2022Neural Light Field Estimation for Street Scenes with Differentiable Virtual Object Insertioncited by 35
  21. 2023Dynamic Mesh-Aware Radiance Fieldscited by 21
  22. 2023Virtual Occlusions Through Implicit Depthcited by 5

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Citing papers per year: 2024: 2; 2025: 3.

5 papers.