Point cloud diffusion for 3D model synthesis. Contribute to openai/point-e development by creating an account on GitHub.
我们利用最新的3D高斯喷洒表示来解决现有缺点,通过利用明确的特性来实现对3D先验的整合。具体而言,我们的方法采用渐进优化策略,包括几何优化阶段和外观细化阶段。在几何优化中,我们在3D几何先验和普通的2D SDS损失的基础上建立了一个粗糙的表示,确保了合理和3D一致的粗糙形状。随后,通过迭代细化获得的高斯函数来丰富细节...
forhuwei}@pku.edu.cnAbstractWe present a probabilistic model for point cloud gen-eration, which is fundamental for various 3D vision taskssuch as shape completion, upsampling, synthesis and dataaugmentation. Inspired by the diffusion process in...
computer-vision 3d-reconstruction diffusion pointclouds 3d-generation diffusion-models point-cloud-completion point-cloud-super-resolution generative-ai Updated Mar 8, 2025 Jupyter Notebook briannemsick / radmap_point_clouds Star 29 Code Issues Pull requests Preprocessing, coordinate frame calibration...
In this paper, we introduce a streamlined deep learning framework for crystal generation: point cloud-based crystal diffusion (PCCD). To test the model’s reliability, we intentionally added noise to our dataset and then used the PCCD to reconstruct the majority of the inputs with only minor ...
The results show that our model can perform well on point cloud completion and is competitive on this task. Our main contributions can be summarized as: (1) We propose a probabilistic model based on diffusion for Terracotta Warriors point cloud completion. The model can infer the conditional ...
This chapter presents the principles of point cloud learning, including the foundations of deep learning and classical neural networks applied to point clouds. The first part covers the basic concepts of deep learning and provides a taxonomy of neural ne
* 题目: Risk-optimized Outlier Removal for Robust Point Cloud Classification* PDF: arxiv.org/abs/2307.1087* 作者: Xinke Li,Junchi Lu* 题目: SCA-PVNet: Self-and-Cross Attention Based Aggregation of Point Cloud and Multi-View for 3D Object Retrieval* PDF: arxiv.org/abs/2307.1060* 作者: ...
3D vision 3D object geometry 1. Introduction Point cloud completion has garnered widespread attention and encompasses various fields including autonomous driving, urban planning, archaeological preservation, medical imaging, and surveying[1],[2],[3],[4],[5],[6]. However, the data acquisition stage...
Denoising diffusion models (DDMs) have shown promising results in 3D point cloud synthesis. 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, ...