PBA VS MegBA

Compare PBA vs MegBA and see what are their differences.

PBA

Photometric Bundle Adjustment for Dense Multi-View Stereo (by cs-9)

MegBA

MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment (by MegviiRobot)
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PBA MegBA
1 1
21 431
- 1.2%
10.0 4.5
over 3 years ago 5 months ago
Python Cuda
- Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

PBA

Posts with mentions or reviews of PBA. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-07.

MegBA

Posts with mentions or reviews of MegBA. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-07.

What are some alternatives?

When comparing PBA and MegBA you can also consider the following projects:

ceres-solver - A large scale non-linear optimization library

DOKSparse - sparse DOK tensors on GPU, pytorch

photobundle - Photometric Bundle Adjustment for Vision-Based SLAM

pixel-perfect-sfm - Pixel-Perfect Structure-from-Motion with Featuremetric Refinement (ICCV 2021, Best Student Paper Award)

photometricBA - Photometric Bundle Adjustment as a refinement step after feature-based Structure-from-Motion

FirstCollisionTimestepRarefiedGasSimulator - This simulator computes all possible intersections for a very small timestep for a particle model

TornadoVM - TornadoVM: A practical and efficient heterogeneous programming framework for managed languages

Scalix - Scalix is a data parallel compute library that automatically scales to the available compute resources.