让普通物体自动变成立体阴影画，生成可识别的图案。
ShadowDraw: From Any Object to Shadow-Drawing Compositional Art
- 通过优化光照与姿态，让物体阴影补全线稿成完整图像。
- 支持真实扫描、生成资产及多物体场景，效果自然且具视觉连贯性。
- 适合艺术设计、创意编程者，可落地于物理装置与动画创作。
我们提出 ShadowDraw，一个将普通 3D 物体转化为阴影绘画构图艺术的框架。给定一个 3D 物体，系统预测场景参数（包括物体姿态和光照），并生成部分线稿，使投射出的阴影能补全为可识别图像。为此，我们优化场景配置以呈现有意义的阴影，利用阴影笔触引导线稿生成，并采用自动评估机制保证阴影-线稿的一致性与视觉质量。实验表明，ShadowDraw 在多种输入上均产生令人信服的结果，涵盖真实扫描、精选数据集以及生成资产，自然扩展至多物体场景、动画和实体部署。本工作提供了一条实用的阴影绘画艺术生成流程，拓展了计算视觉艺术的设计空间，弥合了算法设计与艺术叙事之间的差距。更多结果与端到端真实世界演示请见项目页：https://red-fairy.github.io/ShadowDraw/
原文摘要 · Abstract (English)
We introduce ShadowDraw, a framework that transforms ordinary 3D objects into shadow-drawing compositional art. Given a 3D object, our system predicts scene parameters, including object pose and lighting, together with a partial line drawing, such that the cast shadow completes the drawing into a recognizable image. To this end, we optimize scene configurations to reveal meaningful shadows, employ shadow strokes to guide line drawing generation, and adopt automatic evaluation to enforce shadow-drawing coherence and visual quality. Experiments show that ShadowDraw produces compelling results across diverse inputs, from real-world scans and curated datasets to generative assets, and naturally extends to multi-object scenes, animations, and physical deployments. Our work provides a practical pipeline for creating shadow-drawing art and broadens the design space of computational visual art, bridging the gap between algorithmic design and artistic storytelling. Check out our project page https://red-fairy.github.io/ShadowDraw/ for more results and an end-to-end real-world demonstration of our pipeline!
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