cmu-perceptual-computing-lab
@cmu-perceptual-computing-lab • Open source projects from cmu-perceptual-computing-lab. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.
Portfolio concentration
95%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
15 repos
Visible snapshot
0 repositories updated in the last 90 days.
Leading language
C++
Portfolio mix
C++ (7), Python (3), C# (1)
Average size
2.5K
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
Updated: 2021-01-29(2034d ago)GitHub API fallback15 repositories
95%
of the visible star count comes from this organization's top three repositories.
2.5K
stars per repository in this same snapshot.
C++
is the most common language here, with 0 repositories updated in the last 90 days.
Why this rank
This organization stands out because one flagship repo drives 91% of its visible star count.
Flagship share 91%Breakout repo: openpose
Organization pages work best when you separate portfolio breadth from flagship concentration. In cmu-perceptual-computing-lab's case, the visible top three repositories account for about 95% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is C++ (7), Python (3), C# (1). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
Top Repositories
| # | Repository | Language | Stars |
|---|---|---|---|
| 1 | cmu-perceptual-computing-lab/openpose OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation | C++ | 34.4K |
| 2 | cmu-perceptual-computing-lab/openpose_unity_plugin OpenPose's Unity Plugin for Unity users | C# | 761 |
| 3 | cmu-perceptual-computing-lab/MonocularTotalCapture Code for CVPR19 paper "Monocular Total Capture: Posing Face, Body and Hands in the Wild" | C++ | 676 |
| 4 | cmu-perceptual-computing-lab/openpose_train Training repository for OpenPose | Python | 615 |
| 5 | cmu-perceptual-computing-lab/panoptic-toolbox | Jupyter Notebook | 454 |
| 6 | cmu-perceptual-computing-lab/caffe_rtpose Realtime C++ code for multi-person pose estimation | C++ | 357 |
| 7 | cmu-perceptual-computing-lab/convolutional-pose-machines-release Code repository for Convolutional Pose Machines | Matlab | 116 |
| 8 | cmu-perceptual-computing-lab/caffe_train | C++ | 88 |
| 9 | cmu-perceptual-computing-lab/caffe Caffe: a fast open framework for deep learning. | C++ | 66 |
| 10 | cmu-perceptual-computing-lab/ssp Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction in A Triadic Interaction (CVPR 2020) | Python | 38 |
| 11 | cmu-perceptual-computing-lab/openpose_caffe_train Modified Caffe version for https://github.com/CMU-Perceptual-Computing-Lab/openpose_train | C++ | 32 |
| 12 | cmu-perceptual-computing-lab/foot_keypoint_dataset Website for the foot keypoint dataset: https://cmu-perceptual-computing-lab.github.io/foot_keypoint_dataset/ | HTML | 15 |
| 13 | cmu-perceptual-computing-lab/spatio-temporal-affinity-fields | 9 | |
| 14 | cmu-perceptual-computing-lab/socialSignalPred | Python | 8 |
| 15 | cmu-perceptual-computing-lab/OpenDTAM An open source implementation of DTAM | C++ | 7 |
Next step after the organization read
Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.
Learn and methodology
Keep trust-building context reachable, but behind the first data read instead of ahead of it.
How to read this organization snapshot
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.