Researchers from Codec Avatars Lab, Meta, and Nanyang Technological University have developed URHand, a Universal Relightable Hand model. It achieves photorealistic representation and generalization across viewpoints, poses, illuminations, and identities by combining physically based rendering and neural relighting. The model outperforms baseline methods and showcases adaptability beyond studio data, offering quick personalization. Read about the project and follow the researchers on social media for updates.
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Introducing URHand: A Universal Relightable Hand AI Model
The constant visibility of hands in our daily activities makes them crucial for a sense of self-embodiment. The problem is the need for a digital hand model that is photorealistic, personalized, and relightable. Photorealism ensures a realistic visual representation, personalization caters to individual differences, and reliability allows for a coherent appearance in diverse virtual environments, contributing to a more immersive and natural user experience.
Practical Solutions and Value
URHand is the first Universal Relightable Hand model, designed to generalize across viewpoints, motions, illuminations, and identities. It combines physically based rendering and data-driven appearance modeling using neural relighting, achieving high-fidelity relightable hands. The model enables quick personalization from a phone scan, showcasing its adaptability beyond studio data.
Comparative Performance
Comparing URHand with state-of-the-art 3D hand relighting and reconstruction methods, including RelightableHands and Handy, URHand significantly outperforms baseline methods in per-identity training, reproducing detailed geometry, specularities, and shadows, surpassing the quality of other methods.
AI Solutions for Middle Managers
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For more information, check out the Paper and Project.
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