用一张图生成高精度珊瑚3D模型，助力VR内容高效创作
Coral Model Generation from Single Images for Virtual Reality Applications
- 基于单张图像的深度学习框架，从珊瑚数据集提取几何与纹理特征
- 生成模型在细节、质量与效率上超越传统方法，支持实时交互
- 融合可解释AI，让生成模型成为可交互的虚拟艺术，适合VR/XR场景
随着VR技术快速发展，高质量3D模型需求日益增长。传统方法在大规模定制中面临效率与质量瓶颈。本文提出一种深度学习框架，仅需单张图像即可生成高精度3D珊瑚模型。基于Coral数据集，框架提取几何与纹理特征，完成3D重建，并优化设计与材质融合。通过先进优化与多边形数量控制，确保形状准确性、细节保留及复杂度灵活输出，满足高质量渲染与实时交互需求。项目引入可解释AI（XAI），将AI生成模型转化为可交互的‘艺术品’，在VR与XR中呈现，实时展示珊瑚种类与栖息地信息，增强用户体验。生成模型在细节、视觉质量与效率方面均优于传统方法。本研究为VR内容创作提供智能化方案，降低制作门槛，推动VR广泛应用。同时，该工作为AI生成视觉内容提供了新视角，推进了3D视觉可解释性研究。
原文摘要 · Abstract (English)
With the rapid development of VR technology, the demand for high-quality 3D models is increasing. Traditional methods struggle with efficiency and quality in large-scale customization. This paper introduces a deep-learning framework that generates high-precision 3D coral models from a single image. Using the Coral dataset, the framework extracts geometric and texture features, performs 3D reconstruction, and optimizes design and material blending. Advanced optimization and polygon count control ensure shape accuracy, detail retention, and flexible output for various complexities, catering to high-quality rendering and real-time interaction needs.The project incorporates Explainable AI (XAI) to transform AI-generated models into interactive "artworks," best viewed in VR and XR. This enhances model interpretability and human-machine collaboration. Real-time feedback in VR interactions displays information like coral species and habitat, enriching user experience. The generated models surpass traditional methods in detail, visual quality, and efficiency. This research offers an intelligent approach to 3D content creation for VR, lowering production barriers, and promoting widespread VR applications. Additionally, integrating XAI provides new insights into AI-generated visual content and advances research in 3D vision interpretability.
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