hxwork/H2ONet_Pytorch

[CVPR 2023] H2ONet: Hand-Occlusion-and-Orientation-aware Network for Real-time 3D Hand Mesh Reconstruction, Pytorch implementation.

29
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Experimental

This project helps capture and understand complex hand movements, even when parts of the hand are hidden or at unusual angles. It takes a video or image feed of a hand and outputs a detailed 3D model of its structure and pose in real-time. This is ideal for researchers and engineers developing applications in augmented reality, virtual reality, human-computer interaction, or robotics.

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Use this if you need to accurately track and reconstruct 3D hand poses in real-time, especially in scenarios where hands might be partially obscured or oriented in challenging ways.

Not ideal if your application requires tracking other body parts or objects, or if you need to operate without access to image or video input of the hand.

human-computer-interaction augmented-reality robotics-control motion-capture virtual-reality
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 5 / 25

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66

Forks

2

Language

Python

License

MIT

Last pushed

Dec 01, 2023

Commits (30d)

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