ShadowDraw: From Any Object to Shadow-Drawing Compositional Art

• URL: http://arxiv.org/abs/2512.05110v1
• Date: Thu, 04 Dec 2025 18:59:51 GMT
• Title: ShadowDraw: From Any Object to Shadow-Drawing Compositional Art
• Authors: Rundong Luo, Noah Snavely, Wei-Chiu Ma,
• Abstract summary: We introduce ShadowDraw, a framework that transforms ordinary 3D objects into shadow-drawing compositional art.<n>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.
• Score: 37.2100920237297
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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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