Abstract
3D avatars are important for various virtual reality (VR) and augmented reality (AR) applications. High-fidelity 3D avatars from real people enhance the realism and interactivity of virtual experience. Creating these avatars accurately and efficiently is a challenging problem. A lifelike 3D human model requires precise color representation. An accurate representation of the color is essential to capture the details of human skin, hair, and clothing to match the real people. Traditional methods, such as 3D scanning and multi-image modeling, are costly and complex, limiting their accessibility to an average user. To address this issue, we introduce a novel approach that requires just a single frontal image to generate 3D avatars. Our method tackles critical challenges in the field of single-image 3D avatar generation: color prediction. To achieve better prediction results, we propose a hybrid coloring technique that combines model-based and projection-based methods. This approach enhances 3D avatars’ fidelity and ensures realistic appearances from all viewpoints. Our advancements have achieved better results in quantitative evaluation and rendering results compared to the previous state-of-the-art method. The entire avatar-generating process is also seven times faster than the NeRF-based method. Our research provides an easily accessible but robust method for reconstructing interactive 3D avatars. © 2025 by SCITEPRESS - Science and Technology Publications, Lda.