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
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets
This paper proposes GDPNet, the first hybrid Generative and Discriminative PointNet that extends JEM for point cloud classification and generation.
NeRF2Points: Large-Scale Point Cloud Generation From Street Views' Radiance Field Optimization
Neural Radiance Fields (NeRF) have emerged as a paradigm-shifting methodology for the photorealistic rendering of objects and environments, enabling the synthesis of novel viewpoints with remarkable fidelity.
Enhancing Diffusion-based Point Cloud Generation with Smoothness Constraint
Diffusion models have been popular for point cloud generation tasks.
Exploiting Topological Prior for Boosting Point Cloud Generation
This paper presents an innovative enhancement to the Sphere as Prior Generative Adversarial Network (SP-GAN) model, a state-of-the-art GAN designed for point cloud generation.
RangeLDM: Fast Realistic LiDAR Point Cloud Generation
Autonomous driving demands high-quality LiDAR data, yet the cost of physical LiDAR sensors presents a significant scaling-up challenge.
A Lennard-Jones Layer for Distribution Normalization
We introduce the Lennard-Jones layer (LJL) for the equalization of the density of 2D and 3D point clouds through systematically rearranging points without destroying their overall structure (distribution normalization).
Unveiling Spaces: Architecturally meaningful semantic descriptions from images of interior spaces
There has been a growing adoption of computer vision tools and technologies in architectural design workflows over the past decade.
Fast Training of Diffusion Transformer with Extreme Masking for 3D Point Clouds Generation
Motivated by the inherent redundancy of 3D compared to 2D, we propose FastDiT-3D, a novel masked diffusion transformer tailored for efficient 3D point cloud generation, which greatly reduces training costs.
UNeR3D: Versatile and Scalable 3D RGB Point Cloud Generation from 2D Images in Unsupervised Reconstruction
Our model significantly cuts down the training costs tied to supervised approaches and introduces RGB coloration to 3D point clouds, enriching the visual experience.
WonderJourney: Going from Anywhere to Everywhere
We introduce WonderJourney, a modularized framework for perpetual 3D scene generation.
