pixel-perfect-sfm
MegBA
| pixel-perfect-sfm | MegBA | |
|---|---|---|
| 4 | 1 | |
| 1,246 | 431 | |
| 1.8% | 1.2% | |
| 4.2 | 4.5 | |
| about 2 months ago | 5 months ago | |
| C++ | Cuda | |
| Apache License 2.0 | Apache License 2.0 |
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pixel-perfect-sfm
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On replacing Colmap
Are there alternatives available to the SfM pipeline? https://github.com/cvg/pixel-perfect-sfm for instance takes a deep NN to predict surfaces in the dense step ( not needed for GSplats), is a trained approach for spare reconstruction thinkable, are there other SfM methods that are significantly faster or find more features?
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[advice] lost in the field
If you are interested in camera pose estimation from images, then the state of the art baseline is still Colmap which is used by industry and research. You can checkout concurrent work like https://github.com/cvg/pixel-perfect-sfm. Should be a lot of tutorials and documentation for you to get it running.
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Photometric Bundle Adjustment library?
Finally there is also https://github.com/cvg/pixel-perfect-sfm which does do some photometric/dense refinement, but I think it only works in the featuremetric space. So not exactly photometric.
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Questions for SLAM/SfM for Dense 3D Reconstruction (DSO vs ORB, Monofusion etc.)
I've stumbled upon this and that using DL, and will try to check to simultaneously evaluate them next to developing something using pySLAM. At least that's the current plan.
MegBA
What are some alternatives?
colmap - COLMAP - Structure-from-Motion and Multi-View Stereo
PBA - Photometric Bundle Adjustment for Dense Multi-View Stereo
OpenChisel - An open-source version of the Chisel chunked TSDF library.
DOKSparse - sparse DOK tensors on GPU, pytorch
ov2slam - OV²SLAM is a Fully Online and Versatile Visual SLAM for Real-Time Applications
FirstCollisionTimestepRarefiedGasSimulator - This simulator computes all possible intersections for a very small timestep for a particle model
pyslam - pySLAM contains a monocular Visual Odometry (VO) pipeline in Python. It supports many modern local features based on Deep Learning.
TornadoVM - TornadoVM: A practical and efficient heterogeneous programming framework for managed languages
voxblox - A library for flexible voxel-based mapping, mainly focusing on truncated and Euclidean signed distance fields.
ceres-solver - A large scale non-linear optimization library
MonoRec - Official implementation of the paper: MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera (CVPR 2021)
Scalix - Scalix is a data parallel compute library that automatically scales to the available compute resources.