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 with no code
FrePolad: Frequency-Rectified Point Latent Diffusion for Point Cloud Generation
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.
General Point Model with Autoencoding and Autoregressive
This model is versatile, allowing fine-tuning for downstream point cloud representation tasks, as well as unconditional and conditional generation tasks.
Improving Neural Radiance Field using Near-Surface Sampling with Point Cloud Generation
This paper proposes a near-surface sampling framework to improve the rendering quality of NeRF.
Semantics-aware LiDAR-Only Pseudo Point Cloud Generation for 3D Object Detection
Although LiDAR sensors are crucial for autonomous systems due to providing precise depth information, they struggle with capturing fine object details, especially at a distance, due to sparse and non-uniform data.
Select-and-Combine (SAC): A Novel Multi-Stereo Depth Fusion Algorithm for Point Cloud Generation via Efficient Local Markov Netlets
However, the noises and outliers caused by stereo matching and the heterogenous geometric errors of the poses present a challenge for existing fusion algorithms, since they mostly assume Gaussian errors and predict fused results based on data from local spatial neighborhoods, which may inherit uncertainties from multiple depths resulting in lowered accuracy.
Sketch and Text Guided Diffusion Model for Colored Point Cloud Generation
In this paper, we propose a sketch and text guided probabilistic diffusion model for colored point cloud generation that conditions the denoising process jointly with a hand drawn sketch of the object and its textual description.
4D Millimeter-Wave Radar in Autonomous Driving: A Survey
In an effort to bridge this gap and stimulate future research, this paper presents an exhaustive survey on the utilization of 4D mmWave radar in autonomous driving.
DiffFacto: Controllable Part-Based 3D Point Cloud Generation with Cross Diffusion
We propose a factorization that models independent part style and part configuration distributions and presents a novel cross-diffusion network that enables us to generate coherent and plausible shapes under our proposed factorization.
StarNet: Style-Aware 3D Point Cloud Generation
This paper investigates an open research task of reconstructing and generating 3D point clouds.
FullFormer: Generating Shapes Inside Shapes
Implicit generative models have been widely employed to model 3D data and have recently proven to be successful in encoding and generating high-quality 3D shapes.
