Python · Apache-2.0
Unity-Technologies/Robotics-Object-Pose-Estimation
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
★ 350
Stars
83 forks · 7 open issues
−1.0/wk
Growth · measured
Stars counted between two of our own snapshots roughly a week apart. The repository page gives the exact span.
7.4
Momentum / 100
see the breakdown below
5y ago
Created
last push 4y ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 0.0 | −1.0/wk, log-scaled against a 750/day ceiling |
| Acceleration | 15 | 0.0 | needs 7-day and 30-day rates side by side |
| Freshness | 15 | 0.0 | last push 4y ago; decays to zero at 180 days |
| Scale | 15 | 7.4 | 350 stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 7.4 | sum of the above |
Detail
| Topics | autonomycomputer-visiondeep-learningmachine-learningmanipulationmodel-trainingmotion-planningperceptionphysics-simulationpose-estimationroboticsrobotics-simulationrossimulationsynthetic-datatrajectory-generationtutorialunityur3-robot-armurdf |
| Matched on | Robotics (motion-planning, robotics-simulation) |
| Short window | +-1 stars over 7 days = -0.1/day |
| Long window | +-2 stars over 26 days = -0.1/day |
| Lifetime average | 0.17 stars/day over 2,085 days |
| First seen here | 2026-10-11 |
| Last read | 2d ago |