ET
ethanhe42/epipolar-transformers
Epipolar Transformers (best paper award, CVPR 2020 workshop)
427 38 +0/wk
GitHub
3d 3dposeestimation deep-learning pose-estimation pytorch
Trend
0
Star & Fork Trend (20 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
ethanhe42/epipolar-transformers has +0 stars this period . Velocity data will be available after more historical data is collected.
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Signal-backed technical analysis will be available soon.
| Metric | epipolar-transformers | Olympus | AutoPentest-DRL | multi-class-text-classification-cnn |
|---|---|---|---|---|
| Stars | 427 | 427 | 427 | 426 |
| Forks | 38 | 72 | 112 | 195 |
| Weekly Growth | +0 | +0 | -1 | +0 |
| Language | Jupyter Notebook | Python | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | N/A | BSD-3-Clause | Apache-2.0 |
Capability Radar vs Olympus
epipolar-transformers
Olympus
Maintenance Activity 0
Last code push 707 days ago.
Community Engagement 44
Fork-to-star ratio: 8.9%. 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 MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.