ER
hzwer/ECCV2022-RIFE
ECCV2022 - Real-Time Intermediate Flow Estimation for Video Frame Interpolation
5.4k 535 -1/wk
GitHub
aigc computer-vision deep-learning slomo-filter video-interpolation
Trend
0
Star & Fork Trend (28 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
hzwer/ECCV2022-RIFE has -1 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 | ECCV2022-RIFE | pointnet | graph_nets | tch-rs |
|---|---|---|---|---|
| Stars | 5.4k | 5.4k | 5.4k | 5.3k |
| Forks | 535 | 1.5k | 779 | 419 |
| Weekly Growth | -1 | +2 | +0 | +1 |
| Language | Python | Python | Python | Rust |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | NOASSERTION | Apache-2.0 | Apache-2.0 |
Capability Radar vs pointnet
ECCV2022-RIFE
pointnet
Maintenance Activity 0
Last code push 211 days ago.
Community Engagement 50
Fork-to-star ratio: 9.9%. 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.