YangHai-1218/RADet

Rigidity-Aware Detection for 6D Object Pose Estimation (CVPR 2023)

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/ 100
Emerging

This project helps computer vision engineers more accurately identify the location and orientation of rigid objects in complex, cluttered industrial or robotic scenes. It takes in standard image data (like from BOP datasets) and outputs precise 2D bounding boxes, providing a better starting point for subsequent 6D pose estimation workflows. This is ideal for professionals developing systems for robotic manipulation, quality control, or augmented reality.

No commits in the last 6 months.

Use this if you need to improve the initial 2D object detection accuracy in dense scenes, particularly for rigid objects, before performing 6D pose estimation.

Not ideal if your primary goal is general object detection without a focus on 6D pose estimation or if you are working with highly deformable objects.

robotics industrial-automation computer-vision object-pose-estimation augmented-reality
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 10 / 25

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Stars

43

Forks

4

Language

Python

License

Apache-2.0

Last pushed

Oct 10, 2023

Commits (30d)

0

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