mlsanityData to 7 Oct 2026

Differentiable Surface Rendering via Non-Differentiable Sampling

arXiv 2108.04886 ↗First posted 10 Aug 2021cs.GR cs.CVcited by 28

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Abstract (arXiv)

We present a method for differentiable rendering of 3D surfaces that supports both explicit and implicit representations, provides derivatives at occlusion boundaries, and is fast and simple to implement. The method first samples the surface using non-differentiable rasterization, then applies differentiable, depth-aware point splatting to produce the final image. Our approach requires no differentiable meshing or rasterization steps, making it efficient for large 3D models and applicable to isosurfaces extracted from implicit surface definitions. We demonstrate the effectiveness of our method for implicit-, mesh-, and parametric-surface-based inverse rendering and neural-network training applications. In particular, we show for the first time efficient, differentiable rendering of an isosurface extracted from a neural radiance field (NeRF), and demonstrate surface-based, rather than volume-based, rendering of a NeRF.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 12 of its 41 references that are in the map. First posted on arXiv 10 Aug 2021.

Builds on

12 of 41 references.

References · 12

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervisioncited by 699
  3. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 439
  4. 2017Neural 3D Mesh Renderercited by 437
  5. 2019Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoningcited by 420
  6. 2020Softmax Splatting for Video Frame Interpolationcited by 276
  7. 2019Differentiable Surface Splatting for Point-based Geometry Processingcited by 238
  8. 2019Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderercited by 221
  9. 2019DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracingcited by 179
  10. 2020MeshSDF: Differentiable Iso-Surface Extractioncited by 112
  11. 2019Learning single-image 3D reconstruction by generative modelling of shape, pose and shadingcited by 43
  12. 2016A Versatile Scene Model with Differentiable Visibility Applied to Generative Pose Estimationcited by 42

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 9; 2023: 8; 2024: 6; 2025: 1; 2026: 1.

28 papers.

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  1. 2022MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architecturescited by 308
  2. 2021Hallucinated Neural Radiance Fields in the Wildcited by 130
  3. 2021NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenescited by 119
  4. 2021FENeRF: Face Editing in Neural Radiance Fieldscited by 112
  5. 2022IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Imagescited by 110
  6. 2024GOI: Find 3D Gaussians of Interest with an Optimizable Open-vocabulary Semantic-space Hyperplanecited by 53
  7. 2022Approximate Differentiable Rendering with Algebraic Surfacescited by 44
  8. 2022A Level Set Theory for Neural Implicit Evolution under Explicit Flowscited by 42
  9. 2023NeRFLiX: High-Quality Neural View Synthesis by Learning a Degradation-Driven Inter-viewpoint MiXercited by 29
  10. 2022Differentiable Rendering of Neural SDFs through Reparameterizationcited by 26
  11. 2023Re-ReND: Real-time Rendering of NeRFs across Devicescited by 17
  12. 2022Neural Parameterization for Dynamic Human Head Editingcited by 16
16 more
  1. 2022Spelunking the Deep: Guaranteed Queries on General Neural Implicit Surfaces via Range Analysiscited by 11
  2. 2024Dr.Hair: Reconstructing Scalp-Connected Hair Strands without Pre-training via Differentiable Rendering of Line Segmentscited by 11
  3. 2025CCL-LGS: Contrastive Codebook Learning for 3D Language Gaussian Splattingcited by 11
  4. 2022Plateau-reduced Differentiable Path Tracingcited by 10
  5. 2023Canonical Factors for Hybrid Neural Fieldscited by 8
  6. 2024A Simple Approach to Differentiable Rendering of SDFscited by 7
  7. 2023From NeRFLiX to NeRFLiX++: A General NeRF-Agnostic Restorer Paradigmcited by 6
  8. 2024Benchmarking Implicit Neural Representation and Geometric Rendering in Real-Time RGB-D SLAMcited by 6
  9. 2024DiffCSG: Differentiable CSG via Rasterizationcited by 6
  10. 2022FLNeRF: 3D Facial Landmarks Estimation in Neural Radiance Fieldscited by 2
  11. 2023FastMESH: Fast Surface Reconstruction by Hexagonal Mesh-based Neural Renderingcited by 2
  12. 2023GET3D--: Learning GET3D from Unconstrained Image Collectionscited by 2
  13. 2023High-Quality Real-Time Rendering Using Subpixel Sampling Reconstructioncited by 1
  14. 2023DR-WLC: Dimensionality Reduction cognition for object detection and pose estimation by Watching, Learning and Checkingcited by 0
  15. 2024Deep Neural Implicit Representation of Accessibility for Multi-Axis Manufacturingcited by 0
  16. 2026VEPHand: View-Efficient Photometric Hand Performance Capture at Scalecited by 0