xivo
Open3D
| xivo | Open3D | |
|---|---|---|
| 2 | 11 | |
| 828 | 10,538 | |
| 0.0% | 1.9% | |
| 0.0 | 8.6 | |
| about 1 year ago | 6 days ago | |
| C++ | C++ | |
| GNU General Public License v3.0 or later | MIT |
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.
xivo
-
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.
-
[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.
Open3D
-
Does anyone else agree that the links to the latest development version of Open3D don't work?
I was going to file a bug about another issue, but I have to download the development version. This is why I want this solved quickly. None of the links seem to work: https://github.com/isl-org/Open3D/issues/6259
-
Import many photogrammetry software's scenes into Blender
Open3D (JSON, LOG, PLY) 1
- Open3D v0.17
-
CD PROJEKT RED announce The Witcher Remake in Unreal Engine 5
There's also Open3D (O3D) the point cloud library... http://www.open3d.org/
-
Update: Python code that takes pictures from different view points of a 3D model
would this help?
-
Creating a simple 3d engine to render a car for ML, how hard is it? Sim
http://www.open3d.org/ seems like a good choice. Is there anything better I'm missing?
-
3D Reconstruction of Indoor Environments using SLAM and deep learning on RGB-D Data.
Open3D v0.13.0 http://www.open3d.org/
-
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.
-
[D] Need advice on how to generate HD point clouds visuals for a presentation
I normally use Open3D (http://www.open3d.org/) for point cloud visualization, which besides free view also provides an interface for rendering. For the rotation effect, place your object in the world origin, and the camera at a fixed world position looking towards the object. For every desired angle, rotate your object around the required axis by that angle and render the view. Then combine to a gif or video for presentations.
What are some alternatives?
open_vins - An open source platform for visual-inertial navigation research.
PCL - Point Cloud Library (PCL)
rtabmap - RTAB-Map library and standalone application
pyrender - Easy-to-use glTF 2.0-compliant OpenGL renderer for visualization of 3D scenes.
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)
Meshroom - 3D Reconstruction Software
void-dataset - Visual Odometry with Inertial and Depth (VOID) dataset
three.js - JavaScript 3D Library.
r3live - A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
moderngl - Modern OpenGL binding for Python
SuperPoint_SLAM - SuperPoint + ORB_SLAM2
blender - Official mirror of Blender