mlsanityData to 7 Oct 2026

NeuTex: Neural Texture Mapping for Volumetric Neural Rendering

arXiv 2103.00762 ↗First posted 1 Mar 2021cs.CVcited by 98

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Abstract (arXiv)

Recent work has demonstrated that volumetric scene representations combined with differentiable volume rendering can enable photo-realistic rendering for challenging scenes that mesh reconstruction fails on. However, these methods entangle geometry and appearance in a "black-box" volume that cannot be edited. Instead, we present an approach that explicitly disentangles geometry--represented as a continuous 3D volume--from appearance--represented as a continuous 2D texture map. We achieve this by introducing a 3D-to-2D texture mapping (or surface parameterization) network into volumetric representations. We constrain this texture mapping network using an additional 2D-to-3D inverse mapping network and a novel cycle consistency loss to make 3D surface points map to 2D texture points that map back to the original 3D points. We demonstrate that this representation can be reconstructed using only multi-view image supervision and generates high-quality rendering results. More importantly, by separating geometry and texture, we allow users to edit appearance by simply editing 2D texture maps.

Key facts. Cited by 98 papers in the map (data through 7 Oct 2026). Builds on 32 of its 59 references that are in the map. First posted on arXiv 1 Mar 2021.

Builds on

32 of 59 references.

References · 32

  1. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  2. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  3. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  4. 2020Neural Sparse Voxel Fieldscited by 959
  5. 2019Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representationscited by 864
  6. 2018MVSNet: Depth Inference for Unstructured Multi-view Stereocited by 780
  7. 2019Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervisioncited by 699
  8. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 649
  9. 2018AtlasNet: A Papier-Mach'e Approach to Learning 3D Surface Generationcited by 539
  10. 2020U2-Net: Going Deeper with Nested U-Structure for Salient Object Detectioncited by 410
  11. 2018DeepVoxels: Learning Persistent 3D Feature Embeddingscited by 401
  12. 2018Learning Category-Specific Mesh Reconstruction from Image Collectionscited by 317
20 more
  1. 2018DeepMVS: Learning Multi-view Stereopsiscited by 277
  2. 2019Deferred Neural Rendering: Image Synthesis using Neural Texturescited by 253
  3. 2016Volumetric and Multi-View CNNs for Object Classification on 3D Datacited by 240
  4. 2019Texture Fields: Learning Texture Representations in Function Spacecited by 210
  5. 2018Stereo Magnification: Learning View Synthesis using Multiplane Imagescited by 206
  6. 2020Neural Reflectance Fields for Appearance Acquisitioncited by 196
  7. 2018BA-Net: Dense Bundle Adjustment Networkcited by 173
  8. 2015Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fieldscited by 169
  9. 2019Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awarenesscited by 151
  10. 2019Point-Based Multi-View Stereo Networkcited by 147
  11. 2017SurfaceNet: An End-to-end 3D Neural Network for Multiview Stereopsiscited by 128
  12. 2020Deep Reflectance Volumes: Relightable Reconstructions from Multi-View Photometric Imagescited by 98
  13. 2020Shape and Viewpoint without Keypointscited by 92
  14. 2017SfM-Net: Learning of Structure and Motion from Videocited by 89
  15. 2019Learning a Neural 3D Texture Space from 2D Exemplarscited by 53
  16. 2016Photorealistic Facial Texture Inference Using Deep Neural Networkscited by 32
  17. 2019A Neural Rendering Framework for Free-Viewpoint Relightingcited by 26
  18. 2020Learning Implicit Surface Light Fieldscited by 23
  19. 2020Coupling Explicit and Implicit Surface Representations for Generative 3D Modelingcited by 19
  20. 2018MVPNet: Multi-View Point Regression Networks for 3D Object Reconstruction from A Single Imagecited by 17

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 25; 2023: 25; 2024: 17; 2025: 12; 2026: 10.

98 papers.

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By area:

  1. 2022TensoRF: Tensorial Radiance Fieldscited by 1,275
  2. 2021MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereocited by 735
  3. 2021Neural Fields in Visual Computing and Beyondcited by 539
  4. 2022Point-NeRF: Point-based Neural Radiance Fieldscited by 503
  5. 2021Advances in Neural Renderingcited by 365
  6. 2023DreamEditor: Text-Driven 3D Scene Editing with Neural Fieldscited by 154
  7. 2022NeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for Geometry and Texture Editingcited by 141
  8. 2022StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learningcited by 140
  9. 2021Layered Neural Atlases for Consistent Video Editingcited by 137
  10. 2021Beyond Periodicity: Towards a Unifying Framework for Activations in Coordinate-MLPscited by 134
  11. 2023Vox-E: Text-guided Voxel Editing of 3D Objectscited by 114
  12. 2023Delicate Textured Mesh Recovery from NeRF via Adaptive Surface Refinementcited by 106
38 more
  1. 2021Stylizing 3D Scene via Implicit Representation and HyperNetworkcited by 103
  2. 2022NeRFusion: Fusing Radiance Fields for Large-Scale Scene Reconstructioncited by 99
  3. 2022Compressible-composable NeRF via Rank-residual Decompositioncited by 92
  4. 2023TexFusion: Synthesizing 3D Textures with Text-Guided Image Diffusion Modelscited by 86
  5. 2024TIP-Editor: An Accurate 3D Editor Following Both Text-Prompts And Image-Promptscited by 76
  6. 2022Physically-Based Editing of Indoor Scene Lighting from a Single Imagecited by 62
  7. 2022NeuPhysics: Editable Neural Geometry and Physics from Monocular Videoscited by 50
  8. 2021Learning Neural Light Fields with Ray-Space Embedding Networkscited by 49
  9. 2022UPST-NeRF: Universal Photorealistic Style Transfer of Neural Radiance Fields for 3D Scenecited by 47
  10. 2024Texture-GS: Disentangling the Geometry and Texture for 3D Gaussian Splatting Editingcited by 47
  11. 2022UV Volumes for Real-time Rendering of Editable Free-view Human Performancecited by 43
  12. 2024DeferredGS: Decoupled and Editable Gaussian Splatting with Deferred Shadingcited by 40
  13. 2022Disentangled3D: Learning a 3D Generative Model with Disentangled Geometry and Appearance from Monocular Imagescited by 39
  14. 2022AUV-Net: Learning Aligned UV Maps for Texture Transfer and Synthesiscited by 39
  15. 2023OR-NeRF: Object Removing from 3D Scenes Guided by Multiview Segmentation with Neural Radiance Fieldscited by 34
  16. 2022EditableNeRF: Editing Topologically Varying Neural Radiance Fields by Key Pointscited by 30
  17. 2024GStex: Per-Primitive Texturing of 2D Gaussian Splatting for Decoupled Appearance and Geometry Modelingcited by 30
  18. 2023NeRFLiX: High-Quality Neural View Synthesis by Learning a Degradation-Driven Inter-viewpoint MiXercited by 29
  19. 2023Nuvo: Neural UV Mapping for Unruly 3D Representationscited by 29
  20. 2022Neural Novel Actor: Learning a Generalized Animatable Neural Representation for Human Actorscited by 28
  21. 2022Ray Priors through Reprojection: Improving Neural Radiance Fields for Novel View Extrapolationcited by 26
  22. 2023NeuManifold: Neural Watertight Manifold Reconstruction with Efficient and High-Quality Rendering Supportcited by 25
  23. 2022NeurMiPs: Neural Mixture of Planar Experts for View Synthesiscited by 23
  24. 2024Mani-GS: Gaussian Splatting Manipulation with Triangular Meshcited by 22
  25. 2022Intrinsic Neural Fields: Learning Functions on Manifoldscited by 20
  26. 2023Customize your NeRF: Adaptive Source Driven 3D Scene Editing via Local-Global Iterative Trainingcited by 20
  27. 2023LatentEditor: Text Driven Local Editing of 3D Scenescited by 17
  28. 2022Neural Parameterization for Dynamic Human Head Editingcited by 16
  29. 2023Single-Shot Implicit Morphable Faces with Consistent Texture Parameterizationcited by 16
  30. 2025Neural Shell Texture Splatting: More Details and Fewer Primitivescited by 14
  31. 2023General Neural Gauge Fieldscited by 12
  32. 2022NeAT: Neural Adaptive Tomographycited by 11
  33. 2023TUVF: Learning Generalizable Texture UV Radiance Fieldscited by 9
  34. 2024TexRO: Generating Delicate Textures of 3D Models by Recursive Optimizationcited by 9
  35. 2025PartUV: Part-Based UV Unwrapping of 3D Meshescited by 9
  36. 2022Generative Deformable Radiance Fields for Disentangled Image Synthesis of Topology-Varying Objectscited by 8
  37. 2021Neural Knitworks: Patched Neural Implicit Representation Networkscited by 7
  38. 2021Learning Positional Embeddings for Coordinate-MLPscited by 7

50 most cited of 98 All 98 (JSON)