ShadowDraw: From Any Object to Shadow-Drawing Compositional Art
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Abstract (arXiv)
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!
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 24 of its 54 references that are in the map. First posted on arXiv 4 Dec 2025.
Builds on
24 of 54 references.
References · 24
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,388
- 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
- 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
- 2023ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generationcited by 1,010
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- 2024Evaluating Text-to-Visual Generation with Image-to-Text Generationcited by 465
- 2023Human Preference Score: Better Aligning Text-to-Image Models with Human Preferencecited by 284
- 2022Optimizing Prompts for Text-to-Image Generationcited by 204
- 2021CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoderscited by 186
- 2024MeshLRM: Large Reconstruction Model for High-Quality Meshescited by 138
- 2022Learning to generate line drawings that convey geometry and semanticscited by 82
12 more
- 2019Photo-Sketching: Inferring Contour Drawings from Imagescited by 67
- 2019Learning Temporal Pose Estimation from Sparsely-Labeled Videoscited by 39
- 2024SketchAgent: Language-Driven Sequential Sketch Generationcited by 30
- 2019Im2Pencil: Controllable Pencil Illustration from Photographscited by 18
- 2021DoodleFormer: Creative Sketch Drawing with Transformerscited by 17
- 2015Free-hand Sketch Synthesis with Deformable Stroke Modelscited by 16
- 2023Wired Perspectives: Multi-View Wire Art Embraces Generative AIcited by 16
- 2020Neural Contours: Learning to Draw Lines from 3D Shapescited by 15
- 2021Neural Strokes: Stylized Line Drawing of 3D Shapescited by 13
- 2021Shadow Art Revisited: A Differentiable Rendering Based Approachcited by 10
- 2024Illusion3D: 3D Multiview Illusion with 2D Diffusion Priorscited by 5
- 2025Hand-Shadow Posercited by 3
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Citing papers per year: 2026: 1.
1 paper.