DhyeyR-007/6D-Pose-Estimation
Developed and implemented a regularized 6D pose estimation pipeline based on poseCNN architecture for generalized pose estimation in wild
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.
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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.
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10
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2
Language
Jupyter Notebook
License
MIT
Category
Last pushed
May 08, 2023
Commits (30d)
0
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