SS
fangchangma/self-supervised-depth-completion
ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera"
652 134 +0/wk
GitHub
computer-vision deep-learning depth-completion depth-estimation depth-prediction kitti-dataset lidar pytorch self-supervised-learning
Trend
0
Star & Fork Trend (18 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
fangchangma/self-supervised-depth-completion has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | self-supervised-depth-completion | OmniVinci | ReinforcementLearning.jl | bayesflow |
|---|---|---|---|---|
| Stars | 652 | 652 | 651 | 651 |
| Forks | 134 | 51 | 107 | 82 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Python | Julia | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | Apache-2.0 | NOASSERTION | MIT |
Capability Radar vs OmniVinci
self-supervised-depth-completion
OmniVinci
Maintenance Activity 0
Last code push 1811 days ago.
Community Engagement 100
Fork-to-star ratio: 20.6%. Active community forking and contributing.
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 MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.