colmap
openMVS
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| colmap | openMVS | |
|---|---|---|
| 28 | 3 | |
| 6,720 | 3,085 | |
| 4.3% | - | |
| 9.2 | 3.4 | |
| about 18 hours ago | 30 days ago | |
| C++ | C++ | |
| GNU General Public License v3.0 or later | GNU Affero General Public License v3.0 |
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.
colmap
- Magic123: One Image to High-Quality 3D Object Generation
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Drone mapping is pretty dang cool
Not saying its easy to use, but there is an application gui and it is free: https://github.com/colmap/colmap
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Import many photogrammetry software's scenes into Blender
Colmap (Model folders (BIN and TXT), dense workspaces, NVM, PLY)
- Best options for monocular reconstruction?
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improving camera pose estimation using multiple aruco markers
See colmap for example https://colmap.github.io/
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2D images to 3D Object reconstruction
You're looking into a problem called photogrammetry, and a well-studied one at that. I'd recommend looking into "shape from motion" (sfm); specifically techniques that do "dense reconstruction." I'd recommend COLMAP to start with. It does pose estimation from images (e.g. you point it at a bunch of images and it will figure out the relative poses of the cameras that took them), as well as sparse and dense reconstcution.
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Framework generate 3d meshes from camera images
COLMAP builds dense meshes from a collection of cameras https://colmap.github.io/
- Nerfstudio: A collaboration friendly studio for NeRFs
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Neural Radiance Fields and input shape
I’ve seen references to using COLMAP (https://colmap.github.io/) to estimate camera position/pose, e.g. here
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3D reconstruction of an object from videos/few images
Classical photogrammetry, where I agree with u/tdgros that the way to go is https://colmap.github.io/. There are actually better variants in literature but nothing is more reliable and user-friendly than COLMAP. This will give you a very precise point cloud, that can be meshed if needed.
openMVS
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Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields
I'm anxiously waiting for the code (or for someone to reimplement it open source). Sounds very fun to play with.
I've recently been having fun with OpenMVS [1]. Using Gaussian splatting (which is initialized with a point cloud) would bring it to the next level!
- Generating 3D models from 2D images, where to start?
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New to photogrammetry, getting started?
git clone https://github.com/cdcseacave/openMVS.git
What are some alternatives?
Meshroom - 3D Reconstruction Software
zed-ros2-wrapper - ROS 2 wrapper for the ZED SDK
OpenMVG (open Multiple View Geometry) - open Multiple View Geometry library. Basis for 3D computer vision and Structure from Motion.
meshlab - The open source mesh processing system
Hierarchical-Localization - Visual localization made easy with hloc
ScanRig - Multi-Cameras/Lighting Acquisition Setup for Photogrammetry
nerf - Code release for NeRF (Neural Radiance Fields)
DIY-Multiprotocol-TX-Module - Multiprotocol TX Module (or MULTI-Module) is a 2.4GHz transmitter module which controls many different receivers and models.
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
glog - C++ implementation of the Google logging module
OpenSfM - Open source Structure-from-Motion pipeline
r3live - A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package