Point Cloud Generation
44 papers with code • 4 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Point Cloud Generation
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ShapeNet
JetClass
Latest papers
Fast Point Cloud Generation with Straight Flows
klightz/PSF
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CVPR 2023
We perform evaluations on multiple 3D tasks and find that our PSF performs comparably to the standard diffusion model, outperforming other efficient 3D point cloud generation methods.
LION: Latent Point Diffusion Models for 3D Shape Generation
nv-tlabs/LION
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To advance 3D DDMs and make them useful for digital artists, we require (i) high generation quality, (ii) flexibility for manipulation and applications such as conditional synthesis and shape interpolation, and (iii) the ability to output smooth surfaces or meshes.
Flow-based GAN for 3D Point Cloud Generation from a Single Image
Generating a 3D point cloud from a single 2D image is of great importance for 3D scene understanding applications.
Learning to Generate Realistic LiDAR Point Clouds
We present LiDARGen, a novel, effective, and controllable generative model that produces realistic LiDAR point cloud sensory readings.
Autoregressive 3D Shape Generation via Canonical Mapping
With the capacity of modeling long-range dependencies in sequential data, transformers have shown remarkable performances in a variety of generative tasks such as image, audio, and text generation.
WarpingGAN: Warping Multiple Uniform Priors for Adversarial 3D Point Cloud Generation
yztang4/warpinggan
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CVPR 2022
We propose WarpingGAN, an effective and efficient 3D point cloud generation network.
Attention-based Transformation from Latent Features to Point Clouds
The points generated by AXform do not have the strong 2-manifold constraint, which improves the generation of non-smooth surfaces.
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion
zhaoyanglyu/point_diffusion_refinement
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ICLR 2022
The RFNet refines the coarse output of the CGNet and further improves quality of the completed point cloud.
Flow Plugin Network for conditional generation
pfilo8/flow-plugin-network-for-conditional-generation
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Generative models have gained many researchers' attention in the last years resulting in models such as StyleGAN for human face generation or PointFlow for the 3D point cloud generation.
PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
In this paper, we present a new method that reformulates point cloud completion as a set-to-set translation problem and design a new model, called PoinTr that adopts a transformer encoder-decoder architecture for point cloud completion.
