用顺序笔触生成3D形状，更懂用户的设计意图。
Order Matters: 3D Shape Generation from Sequential VR Sketches
- 捕捉笔触时间顺序，理解设计逻辑。
- 合成数据超2万条，真实草图900对，覆盖四类物体。
- 对不完整草图也能准确生成，适合快速原型设计。
VR草图让用户直接在三维空间中探索和迭代想法，比传统CAD工具更快更直观。但现有草图转形状模型忽略笔触的时间顺序，丢失了结构和设计意图的关键线索。我们提出VRSketch2Shape，首个从序列化VR草图生成3D形状的框架及多类别数据集。贡献包括：(i) 自动化生成任意形状序列化VR草图的流水线；(ii) 超过20,000条合成与900对人工绘制的草图-形状配对数据，涵盖四类物体；(iii) 一种考虑顺序的草图编码器结合基于扩散的3D生成器。该方法在几何保真度上优于先前工作，能以极小监督从合成数据泛化到真实草图，并在部分草图下表现良好。所有数据与模型将开源发布于 https://chenyizi086.github.io/VRSketch2Shape_website。
原文摘要 · Abstract (English)
VR sketching lets users explore and iterate on ideas directly in 3D, offering a faster and more intuitive alternative to conventional CAD tools. However, existing sketch-to-shape models ignore the temporal ordering of strokes, discarding crucial cues about structure and design intent. We introduce VRSketch2Shape, the first framework and multi-category dataset for generating 3D shapes from sequential VR sketches. Our contributions are threefold: (i) an automated pipeline that generates sequential VR sketches from arbitrary shapes, (ii) a dataset of over 20k synthetic and 900 hand-drawn sketch-shape pairs across four categories, and (iii) an order-aware sketch encoder coupled with a diffusion-based 3D generator. Our approach yields higher geometric fidelity than prior work, generalizes effectively from synthetic to real sketches with minimal supervision, and performs well even on partial sketches. All data and models will be released open-source at https://chenyizi086.github.io/VRSketch2Shape_website.
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