DhyeyR-007/6D-Pose-Estimation

Developed and implemented a regularized 6D pose estimation pipeline based on poseCNN architecture for generalized pose estimation in wild

34
/ 100
Emerging

This project helps robots, augmented reality systems, and manufacturing lines understand where objects are in 3D space. By taking a 2D image of an object and its corresponding 3D model, it outputs the object's precise 3D position and orientation. Robotics engineers, AR/VR developers, and manufacturing automation specialists would use this to enable systems to interact with physical objects accurately.

No commits in the last 6 months.

Use this if you need to determine the exact 3D position and orientation of physical objects from camera images for applications like robotic manipulation or augmented reality overlays.

Not ideal if you only need 2D object detection or classification, or if you don't have 3D models of the objects you wish to track.

robotics augmented-reality manufacturing-automation computer-vision 3D-reconstruction
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 13 / 25

How are scores calculated?

Stars

10

Forks

2

Language

Jupyter Notebook

License

MIT

Last pushed

May 08, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/DhyeyR-007/6D-Pose-Estimation"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.