Point cloud completion tool based on dictionary learning. Takes a PCL point cloud surface and fills in gaps or densifies sparse regions by learning from the various surface features of the cloud. This is done using a variation of the k-SVD dictionary learning algorithm that allows for continuous atoms and dealing with unstructured point cloud data.
active 2023-08-17 → 2024-11-29 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 471 days from 2023-08-17 to 2024-11-29. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 2 total, peak 1 in a day. Stars: 12 total, peak 1 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| codearxiv | 2 | 0 | 0 | 2 |
Recent activity
Latest issues, pull requests and releases
- Issue comment#2codearxiv2024-04-08 00:55About how to run the program
- Issue comment#1codearxiv2024-02-16 23:49any reference paper available?
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 12 stars here means stars gained during the window, not the repo's star count.