Open3D
xivo
Our great sponsors
| Open3D | xivo | |
|---|---|---|
| 11 | 2 | |
| 10,408 | 828 | |
| 2.0% | 0.0% | |
| 8.6 | 0.0 | |
| 7 days ago | about 1 year ago | |
| C++ | C++ | |
| MIT | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Open3D
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Import many photogrammetry software's scenes into Blender
Open3D (JSON, LOG, PLY) 1
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Update: Python code that takes pictures from different view points of a 3D model
would this help?
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Show HN: 3dasd – open-source DIY room-scale 3D scanner
Sweet work! If you are interested in 3D reconstruction, have a look at http://www.open3d.org.
- I have an idea for a project, not sure where or how to begin.
xivo
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Unsupervised Depth Completion from Visual Inertial Odometry
Hey there, interested in camera and range sensor fusion for point cloud (depth) completion?
Here is an extended version of our [talk](https://www.youtube.com/watch?v=oBCKO4TH5y0) at ICRA 2020 where we do a step by step walkthrough of our paper Unsupervised Depth Completion from Visual Inertial Odometry (joint work with Fei Xiaohan, Stephanie Tsuei, and Stefano Soatto).
In this talk, we present an unsupervised method (no need for human supervision/annotations) for learning to recover dense point clouds from images, captured by cameras, and sparse point clouds, produced by lidar or tracked by visual inertial odometry (VIO) systems. To illustrate what I mean, here is an [example](https://github.com/alexklwong/unsupervised-depth-completion-visual-inertial-odometry/blob/master/figures/void_teaser.gif?raw=true) of the point clouds produced by our method.
Our method is light-weight (so you can run it on your computer!) and is built on top of [XIVO] (https://github.com/ucla-vision/xivo) our VIO system.
For those interested here are links to the [paper](https://arxiv.org/pdf/1905.08616.pdf), [code](https://github.com/alexklwong/unsupervised-depth-completion-visual-inertial-odometry) and the [dataset](https://github.com/alexklwong/void-dataset) we collected.
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[N][R] ICRA 2020 extended talk for Unsupervised Depth Completion from Visual Inertial Odometry
Our method is light-weight (so you can run it on your computer!) and is built on top of XIVO our VIO system.
What are some alternatives?
PCL - Point Cloud Library (PCL)
pyrender - Easy-to-use glTF 2.0-compliant OpenGL renderer for visualization of 3D scenes.
Meshroom - 3D Reconstruction Software
three.js - JavaScript 3D Library.
moderngl - Modern OpenGL binding for Python
blender - Official mirror of Blender
tinyraytracer - A brief computer graphics / rendering course
tensorflow-wheels - Tensorflow Wheels
meshoptimizer - Mesh optimization library that makes meshes smaller and faster to render
OpenMLDB - OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
meshlab - The open source mesh processing system
open_vins - An open source platform for visual-inertial navigation research.