mlsanityData to 7 Oct 2026

Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs

arXiv 1703.09438 ↗First posted 28 Mar 2017cs.CVcited by 189

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Abstract (arXiv)

We present a deep convolutional decoder architecture that can generate volumetric 3D outputs in a compute- and memory-efficient manner by using an octree representation. The network learns to predict both the structure of the octree, and the occupancy values of individual cells. This makes it a particularly valuable technique for generating 3D shapes. In contrast to standard decoders acting on regular voxel grids, the architecture does not have cubic complexity. This allows representing much higher resolution outputs with a limited memory budget. We demonstrate this in several application domains, including 3D convolutional autoencoders, generation of objects and whole scenes from high-level representations, and shape from a single image.

Key facts. Cited by 189 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Mar 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 72; 2022: 41; 2023: 36; 2024: 19; 2025: 14; 2026: 7.

189 papers.

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  1. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,607
  2. 2023DUSt3R: Geometric 3D Vision Made Easycited by 1,526
  3. 2021PlenOctrees for Real-time Rendering of Neural Radiance Fieldscited by 904
  4. 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
  5. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 459
  6. 20233DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Modelscited by 449
  7. 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 254
  8. 2021Self-Supervised Pretraining of 3D Features on any Point-Cloudcited by 217
  9. 2021Group-Free 3D Object Detection via Transformerscited by 215
  10. 2021NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereocited by 191
  11. 2023XCube: Large-Scale 3D Generative Modeling using Sparse Voxel Hierarchiescited by 183
  12. 2023NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusioncited by 179
38 more
  1. 2021GNeRF: GAN-based Neural Radiance Field without Posed Cameracited by 153
  2. 2022Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Modelscited by 151
  3. 2023Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generationcited by 133
  4. 2023NeRF-DS: Neural Radiance Fields for Dynamic Specular Objectscited by 110
  5. 2021Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networkscited by 101
  6. 2022POCO: Point Convolution for Surface Reconstructioncited by 91
  7. 2021A comprehensive survey on point cloud registrationcited by 84
  8. 2021DiGS : Divergence guided shape implicit neural representation for unoriented point cloudscited by 76
  9. 2022Dual Octree Graph Networks for Learning Adaptive Volumetric Shape Representationscited by 71
  10. 2022DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Imagescited by 69
  11. 2021Deep Implicit Moving Least-Squares Functions for 3D Reconstructioncited by 67
  12. 2021ROCA: Robust CAD Model Retrieval and Alignment from a Single Imagecited by 66
  13. 2021SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networkscited by 59
  14. 2025Bolt3D: Generating 3D Scenes in Secondscited by 57
  15. 2023OctreeOcc: Efficient and Multi-Granularity Occupancy Prediction Using Octree Queriescited by 48
  16. 2021FiG-NeRF: Figure-Ground Neural Radiance Fields for 3D Object Category Modellingcited by 47
  17. 2022GIFS: Neural Implicit Function for General Shape Representationcited by 45
  18. 2021Learning Generative Models of Textured 3D Meshes from Real-World Imagescited by 44
  19. 2022Towards High-Fidelity Single-view Holistic Reconstruction of Indoor Scenescited by 43
  20. 2024L3DG: Latent 3D Gaussian Diffusioncited by 42
  21. 2021Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentationcited by 40
  22. 2021ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generatorscited by 40
  23. 2021Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape Retrieval from a Single Imagecited by 39
  24. 2024LATTE3D: Large-scale Amortized Text-To-Enhanced3D Synthesiscited by 39
  25. 2021SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Datacited by 38
  26. 2021Octree Transformer: Autoregressive 3D Shape Generation on Hierarchically Structured Sequencescited by 38
  27. 2021Multiresolution Deep Implicit Functions for 3D Shape Representationcited by 35
  28. 2022Reconstructing Hand-Held Objects from Monocular Videocited by 35
  29. 2023Vision Transformers with Mixed-Resolution Tokenizationcited by 35
  30. 2022Neural Template: Topology-aware Reconstruction and Disentangled Generation of 3D Meshescited by 34
  31. 2021Learning Parallel Dense Correspondence from Spatio-Temporal Descriptors for Efficient and Robust 4D Reconstructioncited by 31
  32. 2022GenSDF: Two-Stage Learning of Generalizable Signed Distance Functionscited by 30
  33. 2023ZeroShape: Regression-based Zero-shot Shape Reconstructioncited by 30
  34. 2021RetrievalFuse: Neural 3D Scene Reconstruction with a Databasecited by 28
  35. 2021Fast and Explicit Neural View Synthesiscited by 28
  36. 2023NVFi: Neural Velocity Fields for 3D Physics Learning from Dynamic Videoscited by 28
  37. 20223PSDF: Three-Pole Signed Distance Function for Learning Surfaces with Arbitrary Topologiescited by 27
  38. 2021LegoFormer: Transformers for Block-by-Block Multi-view 3D Reconstructioncited by 25

50 most cited of 189 All 189 (JSON)