Visualizing and understanding point cloud data, subsequently performing deep learning tasks on it.
-
Updated
Aug 19, 2020 - Jupyter Notebook
Visualizing and understanding point cloud data, subsequently performing deep learning tasks on it.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
This is a final project for CS 674: Intelligent Visual Computing.
A point cloud generator for various 3d shapes
Group Project for 3D Spatial Learning Practical Course at TUM
This report contains a comprehensive study on unsupervised feature learning using various types of autoencoders.
awesome list of multi-view deep learning papers for 3D understanding and generation
This repository contains 3D-Unet Based segmentation models with different settings. I'll be comparing different models with different settings.
Explore the World in 3D: 3DPointCloudLab is your gateway to the fascinating universe of 3D depth maps and point clouds. Whether you're a researcher, developer, or 3D enthusiast, our repository offers a treasure trove of tools, techniques, and insights dedicated to the exploration and manipulation of 3D spatial data.
PL-Net3D: Robust 3D Object Class Recognition Using Geometric Models
A Framework for Generalized Steady State Neural Fluid Simulations
AIRI_pottery
Pytorch Implementation of Learning Local Shape Descriptors from Part Correspondences(ToG 2017, H Huang et al.): https://people.cs.umass.edu/~hbhuang/local_mvcnn/
Code and Datasets for 3D Shape Completion related publications
GRNet: Geometric Relation Network for 3D Object Detection from Point Clouds
Octree Transformer: Autoregressive 3D Shape Generation on Hierarchically Structured Sequences - CVPRW: StruCo3D, 2023
PointRCNN configured to Argoverse/Custom dataset
Add a description, image, and links to the 3d-deep-learning topic page so that developers can more easily learn about it.
To associate your repository with the 3d-deep-learning topic, visit your repo's landing page and select "manage topics."