mlsanityData to 14 Oct 2026

DOF-GS:Adjustable Depth-of-Field 3D Gaussian Splatting for Post-Capture Refocusing, Defocus Rendering and Blur Removal

arXiv 2405.17351 ↗First posted 27 May 2024cs.CVcited by 8

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Abstract (arXiv)

3D Gaussian Splatting (3DGS) techniques have recently enabled high-quality 3D scene reconstruction and real-time novel view synthesis. These approaches, however, are limited by the pinhole camera model and lack effective modeling of defocus effects. Departing from this, we introduce DOF-GS--a new 3DGS-based framework with a finite-aperture camera model and explicit, differentiable defocus rendering, enabling it to function as a post-capture control tool. By training with multi-view images with moderate defocus blur, DOF-GS learns inherent camera characteristics and reconstructs sharp details of the underlying scene, particularly, enabling rendering of varying DOF effects through on-demand aperture and focal distance control, post-capture and optimization. Additionally, our framework extracts circle-of-confusion cues during optimization to identify in-focus regions in input views, enhancing the reconstructed 3D scene details. Experimental results demonstrate that DOF-GS supports post-capture refocusing, adjustable defocus and high-quality all-in-focus rendering, from multi-view images with uncalibrated defocus blur.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 20 of its 32 references that are in the map. First posted on arXiv 27 May 2024.

Builds on

20 of 32 references.

References · 20

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  2. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  3. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  4. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,613
  5. 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,465
  6. 2023Mip-Splatting: Alias-free 3D Gaussian Splattingcited by 667
  7. 2023Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splattingcited by 476
  8. 2021NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Imagescited by 336
  9. 2022MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architecturescited by 311
  10. 20244D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenescited by 189
  11. 2021Deblur-NeRF: Neural Radiance Fields from Blurry Imagescited by 179
  12. 2022DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenescited by 103
8 more
  1. 2022DP-NeRF: Deblurred Neural Radiance Field with Physical Scene Priorscited by 70
  2. 2024Deblurring 3D Gaussian Splattingcited by 66
  3. 2023Tetra-NeRF: Representing Neural Radiance Fields Using Tetrahedracited by 57
  4. 2024BAGS: Blur Agnostic Gaussian Splatting through Multi-Scale Kernel Modelingcited by 42
  5. 2022DoF-NeRF: Depth-of-Field Meets Neural Radiance Fieldscited by 26
  6. 2022PDRF: Progressively Deblurring Radiance Field for Fast and Robust Scene Reconstruction from Blurry Imagescited by 14
  7. 2024Time-Efficient Light-Field Acquisition Using Coded Aperture and Eventscited by 9
  8. 2022NeRFocus: Neural Radiance Field for 3D Synthetic Defocuscited by 8

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 5.

8 papers.