mlsanityData to 14 Oct 2026

FrePolad: Frequency-Rectified Point Latent Diffusion for Point Cloud Generation

arXiv 2311.12090 ↗First posted 20 Nov 2023cs.CVcited by 9

On the map: Diffusion models → 3D, point cloud and scene generation

Abstract (arXiv)

We propose FrePolad: frequency-rectified point latent diffusion, a point cloud generation pipeline integrating a variational autoencoder (VAE) with a denoising diffusion probabilistic model (DDPM) for the latent distribution. FrePolad simultaneously achieves high quality, diversity, and flexibility in point cloud cardinality for generation tasks while maintaining high computational efficiency. The improvement in generation quality and diversity is achieved through (1) a novel frequency rectification via spherical harmonics designed to retain high-frequency content while learning the point cloud distribution; and (2) a latent DDPM to learn the regularized yet complex latent distribution. In addition, FrePolad supports variable point cloud cardinality by formulating the sampling of points as conditional distributions over a latent shape distribution. Finally, the low-dimensional latent space encoded by the VAE contributes to FrePolad's fast and scalable sampling. Our quantitative and qualitative results demonstrate FrePolad's state-of-the-art performance in terms of quality, diversity, and computational efficiency. Project page: https://chenliang-zhou.github.io/FrePolad/.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 82 of its 103 references that are in the map. First posted on arXiv 20 Nov 2023.

Builds on

82 of 103 references.

Closest ancestors · 5

Same direction, newest first

  1. 2023DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation4 Jul
  2. 2022Fast Point Cloud Generation with Straight Flows4 Dec
  3. 2022LION: Latent Point Diffusion Models for 3D Shape Generation12 Oct
  4. 2022DreamFusion: Text-to-3D using 2D Diffusion29 Sep
  5. 2021Diffusion Probabilistic Models for 3D Point Cloud Generation2 Mar

Other references · 77

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  6. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  7. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  8. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
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  11. 2018Neural Ordinary Differential Equationscited by 3,779
  12. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,253
38 more
  1. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,897
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  3. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,611
  4. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,200
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  6. 2018Glow: Generative Flow with Invertible 1x1 Convolutionscited by 1,545
  7. 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,476
  8. 2019Generating Diverse High-Fidelity Images with VQ-VAE-2cited by 1,387
  9. 2018On the Spectral Bias of Neural Networkscited by 1,341
  10. 2021Cascaded Diffusion Models for High Fidelity Image Generationcited by 1,163
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  12. 2014NICE: Non-linear Independent Components Estimationcited by 1,058
  13. 2016A Point Set Generation Network for 3D Object Reconstruction from a Single Imagecited by 979
  14. 2022Autoregressive Image Generation using Residual Quantizationcited by 722
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  19. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Modelscited by 521
  20. 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
  21. 2019PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flowscited by 488
  22. 2022MagicVideo: Efficient Video Generation With Latent Diffusion Modelscited by 465
  23. 2021Diffusion Autoencoders: Toward a Meaningful and Decodable Representationcited by 449
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  31. 2023Spherical Fourier Neural Operators: Learning Stable Dynamics on the Spherecited by 233
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  33. 2020Focal Frequency Loss for Image Reconstruction and Synthesiscited by 206
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  38. 2021Symbolic Music Generation with Diffusion Modelscited by 154

50 most cited of 77 All 77 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 4; 2026: 4.

9 papers.

  1. 2024Efficient and Scalable Point Cloud Generation with Sparse Point-Voxel Diffusion Modelscited by 7
  2. 2025Terra: Explorable Native 3D World Model with Point Latentscited by 4
  3. 2025MFM-point: Multi-scale Flow Matching for Point Cloud Generationcited by 3
  4. 2026Trajectory Consistency for One-Step Generation on Euler Mean Flowscited by 2
  5. 2026BrickAnything: Geometry-Conditioned Buildable Brick Generation with Structure-Aware Tokenizationcited by 2
  6. 2026Quartet of Diffusions: Structure-Aware Point Cloud Generation through Part and Symmetry Guidancecited by 1
  7. 2025TFDM: Time-Variant Frequency-Based Point Cloud Diffusion with Mambacited by 0
  8. 2025FreNBRDF: A Frequency-Rectified Neural Material Representationcited by 0
  9. 2026PrintAnything: Learning an Intermediate Representation for 3D printing G-code Generationcited by 0

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