MO
astra-vision/MonoScene
[CVPR 2022] "MonoScene: Monocular 3D Semantic Scene Completion": 3D Semantic Occupancy Prediction from a single image
802 76 +0/wk
GitHub
2d-to-3d computer-vision cvpr2022 cvpr22 deep-learning kitti-360 mayavi monocular nyu-depth-v2 occupancy-prediction pytorch semantic-kitti
Trend
0
Star & Fork Trend (170 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
astra-vision/MonoScene has +0 stars this period . Velocity data will be available after more historical data is collected.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | MonoScene | makeMoE | depyf | 365-Days-Computer-Vision-Learning-Linkedin-Post |
|---|---|---|---|---|
| Stars | 802 | 802 | 802 | 801 |
| Forks | 76 | 93 | 28 | 207 |
| Weekly Growth | +0 | +0 | +1 | +0 |
| Language | Python | Jupyter Notebook | Python | N/A |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | MIT | MIT | N/A |
Capability Radar vs makeMoE
MonoScene
makeMoE
Maintenance Activity 90
Last code push 25 days ago.
Community Engagement 47
Fork-to-star ratio: 9.5%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.