mlsanityData to 7 Oct 2026

DoF-NeRF: Depth-of-Field Meets Neural Radiance Fields

arXiv 2208.00945 ↗First posted 1 Aug 2022cs.CVcited by 26

Not on the map. Why?

Abstract (arXiv)

Neural Radiance Field (NeRF) and its variants have exhibited great success on representing 3D scenes and synthesizing photo-realistic novel views. However, they are generally based on the pinhole camera model and assume all-in-focus inputs. This limits their applicability as images captured from the real world often have finite depth-of-field (DoF). To mitigate this issue, we introduce DoF-NeRF, a novel neural rendering approach that can deal with shallow DoF inputs and can simulate DoF effect. In particular, it extends NeRF to simulate the aperture of lens following the principles of geometric optics. Such a physical guarantee allows DoF-NeRF to operate views with different focus configurations. Benefiting from explicit aperture modeling, DoF-NeRF also enables direct manipulation of DoF effect by adjusting virtual aperture and focus parameters. It is plug-and-play and can be inserted into NeRF-based frameworks. Experiments on synthetic and real-world datasets show that, DoF-NeRF not only performs comparably with NeRF in the all-in-focus setting, but also can synthesize all-in-focus novel views conditioned on shallow DoF inputs. An interesting application of DoF-NeRF to DoF rendering is also demonstrated. The source code will be made available at https://github.com/zijinwuzijin/DoF-NeRF.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). Builds on 36 of its 53 references that are in the map. First posted on arXiv 1 Aug 2022.

Builds on

36 of 53 references.

References · 36

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  2. 2021Vision Transformers for Dense Predictioncited by 1,789
  3. 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,230
  4. 2016A Point Set Generation Network for 3D Object Reconstruction from a Single Imagecited by 972
  5. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 961
  6. 2019Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representationscited by 864
  7. 2020NeRF++: Analyzing and Improving Neural Radiance Fieldscited by 857
  8. 2020GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fieldscited by 784
  9. 2020Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenescited by 750
  10. 2021Depth-supervised NeRF: Fewer Views and Faster Training for Freecited by 732
  11. 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 688
  12. 2019Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelinescited by 672
24 more
  1. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 649
  2. 2021FastNeRF: High-Fidelity Neural Rendering at 200FPScited by 510
  3. 2020Space-time Neural Irradiance Fields for Free-Viewpoint Videocited by 414
  4. 2018DeepVoxels: Learning Persistent 3D Feature Embeddingscited by 401
  5. 2021NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Imagescited by 336
  6. 2018Learning Category-Specific Mesh Reconstruction from Image Collectionscited by 317
  7. 2018Generating 3D faces using Convolutional Mesh Autoencoderscited by 267
  8. 2020Single-View View Synthesis with Multiplane Imagescited by 263
  9. 2019DeepView: View Synthesis with Learned Gradient Descentcited by 253
  10. 2018Stereo Magnification: Learning View Synthesis using Multiplane Imagescited by 206
  11. 2021Self-Calibrating Neural Radiance Fieldscited by 204
  12. 2019Neural Volumes: Learning Dynamic Renderable Volumes from Imagescited by 173
  13. 2019Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Imagescited by 164
  14. 2021HDR-NeRF: High Dynamic Range Neural Radiance Fieldscited by 113
  15. 2018Synthetic Depth-of-Field with a Single-Camera Mobile Phonecited by 70
  16. 2016Unsupervised Learning of 3D Structure from Imagescited by 67
  17. 2020Rendering Natural Camera Bokeh Effect with Deep Learningcited by 57
  18. 2022BokehMe: When Neural Rendering Meets Classical Renderingcited by 48
  19. 2019Synthetic Defocus and Look-Ahead Autofocus for Casual Videographycited by 28
  20. 2020AIM 2020 Challenge on Rendering Realistic Bokehcited by 26
  21. 2019SteReFo: Efficient Image Refocusing with Stereo Visioncited by 25
  22. 2020BGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokehcited by 19
  23. 2021Stacked Deep Multi-Scale Hierarchical Network for Fast Bokeh Effect Rendering from a Single Imagecited by 18
  24. 2022NeRFocus: Neural Radiance Field for 3D Synthetic Defocuscited by 8

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 10; 2025: 7; 2026: 2.

26 papers.

Sort:

  1. 2024DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalizationcited by 256
  2. 2023HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Samplingcited by 173
  3. 2024Deblurring 3D Gaussian Splattingcited by 66
  4. 2023NeRFLiX: High-Quality Neural View Synthesis by Learning a Degradation-Driven Inter-viewpoint MiXercited by 29
  5. 2023Mirror-NeRF: Learning Neural Radiance Fields for Mirrors with Whitted-Style Ray Tracingcited by 22
  6. 2023HumanNeRF-SE: A Simple yet Effective Approach to Animate HumanNeRF with Diverse Posescited by 12
  7. 2024Sharp-NeRF: Grid-based Fast Deblurring Neural Radiance Fields Using Sharpness Priorcited by 12
  8. 2024Cinematic Gaussians: Real-Time HDR Radiance Fields with Depth of Fieldcited by 12
  9. 2023Digging into Depth Priors for Outdoor Neural Radiance Fieldscited by 11
  10. 2023Inverting the Imaging Process by Learning an Implicit Camera Modelcited by 10
  11. 2024DOF-GS:Adjustable Depth-of-Field 3D Gaussian Splatting for Post-Capture Refocusing, Defocus Rendering and Blur Removalcited by 8
  12. 2025CoMoGaussian: Continuous Motion-Aware Gaussian Splatting from Motion-Blurred Imagescited by 7
14 more
  1. 2023From NeRFLiX to NeRFLiX++: A General NeRF-Agnostic Restorer Paradigmcited by 6
  2. 2024Dynamic Neural Radiance Field From Defocused Monocular Videocited by 6
  3. 2025DoF-Gaussian: Controllable Depth-of-Field for 3D Gaussian Splattingcited by 6
  4. 2024S-DyRF: Reference-Based Stylized Radiance Fields for Dynamic Scenescited by 3
  5. 2024CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Imagescited by 2
  6. 2024SGCNeRF: Few-Shot Neural Rendering via Sparse Geometric Consistency Guidancecited by 1
  7. 2024ExFMan: Rendering 3D Dynamic Humans with Hybrid Monocular Blurry Frames and Eventscited by 1
  8. 2025Dynamic Gaussian Splatting from Defocused and Motion-blurred Monocular Videoscited by 1
  9. 2025Dual-Camera All-in-Focus Neural Radiance Fieldscited by 0
  10. 2025NeurNCD: Novel Class Discovery via Implicit Neural Representationcited by 0
  11. 2025Every Camera Effect, Every Time, All at Once: 4D Gaussian Ray Tracing for Physics-based Camera Effect Data Generationcited by 0
  12. 2025DISK: Differentiable Sparse Kernel Complex for Efficient Spatially-Variant Convolutioncited by 0
  13. 2026EDoF-NeRF: extended depth-of-field neural radiance fields using a coded aperture cameracited by 0
  14. 2026Light Field Primitive for Novel View Synthesiscited by 0