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.

Unity-Technologies
Unity-Technologies
Date Created 2021-02-19 (4 years ago)
Commits 102 (last one 3 years ago)
Stargazers 315 (1 this week)
Watchers 14 (0 this week)
Forks 77
License apache-2.0
Ranking

RepositoryStats indexes 637,312 repositories, of these Unity-Technologies/Robotics-Object-Pose-Estimation is ranked #135,540 (79th percentile) for total stargazers, and #151,999 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #23,828/130,523.

Unity-Technologies/Robotics-Object-Pose-Estimation is also tagged with popular topics, for these it's ranked: deep-learning (#2,829/8842),  machine-learning (#2,723/8452),  computer-vision (#972/3311),  unity (#560/2165),  tutorial (#542/1572),  robotics (#376/1413),  simulation (#218/1081),  ros (#184/802),  pose-estimation (#105/353),  physics-simulation (#36/167),  motion-planning (#42/164)

Other Information

Unity-Technologies/Robotics-Object-Pose-Estimation has Github issues enabled, there are 7 open issues and 26 closed issues.

There have been 1 release, the latest one was published on 2021-02-19 (4 years ago) with the name Object Pose Estimation Tutorial.

Star History

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Github watchers over time, collection started in '23

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Recent Commit History

5 commits on the default branch (main) since jan '22

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Issue History

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Languages

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Unity-Technologies/Robotics-Object-Pose-Estimation

updated: 2025-04-04 @ 08:40pm, id: 340219153 / R_kgDOFEdVEQ