ov2slam
colmap
| ov2slam | colmap | |
|---|---|---|
| 1 | 28 | |
| 545 | 6,794 | |
| - | 2.7% | |
| 0.0 | 9.2 | |
| almost 3 years ago | 4 days ago | |
| C++ | C++ | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
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ov2slam
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Questions for SLAM/SfM for Dense 3D Reconstruction (DSO vs ORB, Monofusion etc.)
For instance you could go with : https://github.com/ov2slam/ov2slam , add some processing on the keyframes for depth maps computation and then fuse the depth maps in a TSDF using https://github.com/personalrobotics/OpenChisel or https://github.com/ethz-asl/voxblox
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.
What are some alternatives?
pyslam - pySLAM contains a monocular Visual Odometry (VO) pipeline in Python. It supports many modern local features based on Deep Learning.
Meshroom - 3D Reconstruction Software
pixel-perfect-sfm - Pixel-Perfect Structure-from-Motion with Featuremetric Refinement (ICCV 2021, Best Student Paper Award)
OpenMVG (open Multiple View Geometry) - open Multiple View Geometry library. Basis for 3D computer vision and Structure from Motion.
openvslam - OpenVSLAM: A Versatile Visual SLAM Framework
Hierarchical-Localization - Visual localization made easy with hloc
OpenChisel - An open-source version of the Chisel chunked TSDF library.
nerf - Code release for NeRF (Neural Radiance Fields)
voxblox - A library for flexible voxel-based mapping, mainly focusing on truncated and Euclidean signed distance fields.
openMVS - open Multi-View Stereo reconstruction library
MonoRec - Official implementation of the paper: MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera (CVPR 2021)
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more