The rise of AR/VR has led to an increased demand for 3D content. However, the traditional method of creating 3D content using Computer-Aided Design (CAD) is a labor-intensive and skill-demanding process, making it difficult to use for novice users. Sketch-based 3D modeling provides a promising solution by leveraging the intuitive nature of human-computer interaction. However, generating high-quality content that accurately reflects the creator's ideas can be challenging due to the sparsity and ambiguity of sketches. Furthermore, novice users often find it challenging to create accurate drawings from multiple perspectives or follow step-by-step instructions in existing methods. To address this, we introduce a groundbreaking end-to-end approach in our work, enabling 3D modeling from a single free-hand sketch, Deep3DSketch+$\backslash$+. The issue of sparsity and ambiguity using single sketch is resolved in our approach by leveraging the symmetry prior and structural-aware shape discriminator. We conducted comprehensive experiments on diverse datasets, including both synthetic and real data, to validate the efficacy of our approach and demonstrate its state-of-the-art (SOTA) performance. Users are also more satisfied with results generated by our approach according to our user study. We believe our approach has the potential to revolutionize the process of 3D modeling by offering an intuitive and easy-to-use solution for novice users.

翻译：AR/VR的兴起带动了对三维内容日益增长的需求。然而，传统利用计算机辅助设计（CAD）进行三维内容创建的方法是一个劳动密集且技能要求高的过程，使得新手用户难以使用。基于草图的三维建模利用人机交互的直观性提供了有前景的解决方案。然而，由于草图的稀疏性和歧义性，生成能准确反映创作者意图的高质量内容颇具挑战。此外，新手用户常发现难以从多视角绘制精确的草图，或难以遵循现有方法中的分步指导。为解决此问题，我们提出了一项突破性的端到端方法，能从单幅手绘草图进行三维建模——Deep3DSketch++。通过利用对称性先验和结构感知形状判别器，我们解决了单幅草图稀疏性和歧义性的问题。我们在包含合成数据和真实数据的多个数据集上进行了全面实验，验证了方法的有效性，并展示了其最先进的（SOTA）性能。根据用户研究，用户对我们方法生成的结果满意度也更高。我们相信，通过为新手用户提供直观易用的解决方案，我们的方法有望革新三维建模流程。