mlsanityData to 14 Oct 2026

Implicit Geometric Regularization for Learning Shapes

arXiv 2002.10099 ↗First posted 24 Feb 2020cs.LG cs.CV cs.GRcited by 710

Not on the map. Why?

Abstract (arXiv)

Representing shapes as level sets of neural networks has been recently proved to be useful for different shape analysis and reconstruction tasks. So far, such representations were computed using either: (i) pre-computed implicit shape representations; or (ii) loss functions explicitly defined over the neural level sets. In this paper we offer a new paradigm for computing high fidelity implicit neural representations directly from raw data (i.e., point clouds, with or without normal information). We observe that a rather simple loss function, encouraging the neural network to vanish on the input point cloud and to have a unit norm gradient, possesses an implicit geometric regularization property that favors smooth and natural zero level set surfaces, avoiding bad zero-loss solutions. We provide a theoretical analysis of this property for the linear case, and show that, in practice, our method leads to state of the art implicit neural representations with higher level-of-details and fidelity compared to previous methods.

Key facts. Cited by 710 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Feb 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 78; 2022: 140; 2023: 196; 2024: 154; 2025: 97; 2026: 45.

710 papers.

Sort:

By area:

  1. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,712
  2. 2021Efficient Geometry-aware 3D Generative Adversarial Networkscited by 1,205
  3. 2021Volume Rendering of Neural Implicit Surfacescited by 996
  4. 2021PlenOctrees for Real-time Rendering of Neural Radiance Fieldscited by 905
  5. 2021UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstructioncited by 646
  6. 2021RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputscited by 615
  7. 2021Neural Fields in Visual Computing and Beyondcited by 540
  8. 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 470
  9. 2023Neuralangelo: High-Fidelity Neural Surface Reconstructioncited by 467
  10. 2023FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objectscited by 429
  11. 2021Advances in Neural Renderingcited by 365
  12. 2021PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relightingcited by 335
38 more
  1. 2022NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstructioncited by 314
  2. 2023UniSim: A Neural Closed-Loop Sensor Simulatorcited by 297
  3. 2021StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generationcited by 289
  4. 20223D Neural Field Generation using Triplane Diffusioncited by 274
  5. 2021I M Avatar: Implicit Morphable Head Avatars from Videoscited by 231
  6. 2021SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapescited by 221
  7. 2023BakedSDF: Meshing Neural SDFs for Real-Time View Synthesiscited by 221
  8. 2022Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstructioncited by 212
  9. 2021Shape As Points: A Differentiable Poisson Solvercited by 187
  10. 2022PointAvatar: Deformable Point-based Head Avatars from Videoscited by 184
  11. 2021SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networkscited by 181
  12. 2022SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse Viewscited by 177
  13. 2023NICER-SLAM: Neural Implicit Scene Encoding for RGB SLAMcited by 164
  14. 2023NeRO: Neural Geometry and BRDF Reconstruction of Reflective Objects from Multiview Imagescited by 163
  15. 2021H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motioncited by 157
  16. 2023DreamEditor: Text-Driven 3D Scene Editing with Neural Fieldscited by 155
  17. 2022Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentationcited by 152
  18. 2023BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objectscited by 148
  19. 2022SelfRecon: Self Reconstruction Your Digital Avatar from Monocular Videocited by 144
  20. 2021BACON: Band-limited Coordinate Networks for Multiscale Scene Representationcited by 143
  21. 2022NeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for Geometry and Texture Editingcited by 142
  22. 2021Modulated Periodic Activations for Generalizable Local Functional Representationscited by 140
  23. 2022ARAH: Animatable Volume Rendering of Articulated Human SDFscited by 139
  24. 2023NeuSG: Neural Implicit Surface Reconstruction with 3D Gaussian Splatting Guidancecited by 138
  25. 2021Improving neural implicit surfaces geometry with patch warpingcited by 137
  26. 2023Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decompositioncited by 134
  27. 2023GO-SLAM: Global Optimization for Consistent 3D Instant Reconstructioncited by 133
  28. 2023SelfOcc: Self-Supervised Vision-Based 3D Occupancy Predictioncited by 133
  29. 2022Neural Wavelet-domain Diffusion for 3D Shape Generationcited by 132
  30. 2023DiffusioNeRF: Regularizing Neural Radiance Fields with Denoising Diffusion Modelscited by 127
  31. 2022Photorealistic Monocular 3D Reconstruction of Humans Wearing Clothingcited by 126
  32. 2022NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal Priorscited by 125
  33. 2022Neural 3D Scene Reconstruction with the Manhattan-world Assumptioncited by 123
  34. 2023StreetSurf: Extending Multi-view Implicit Surface Reconstruction to Street Viewscited by 120
  35. 2022Semantic-Aware Implicit Neural Audio-Driven Video Portrait Generationcited by 119
  36. 2022MagicPony: Learning Articulated 3D Animals in the Wildcited by 112
  37. 2022IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Imagescited by 111
  38. 2022EVA3D: Compositional 3D Human Generation from 2D Image Collectionscited by 111

50 most cited of 710 All 710 (JSON)