# Inverse Procedural Modeling of Facade Layouts

arXiv: https://arxiv.org/abs/1308.0419 · HTML: https://mlsanity.com/paper/1308.0419/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Aug 2013.

## Built on by (most cited first, 8 of 8)

- [ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives](https://mlsanity.com/paper/2305.05661/) (2023)
- [FaccAID: A Transformer Model for Neuro-Symbolic Facade Reconstruction](https://mlsanity.com/paper/2406.01829/) (2024)
- [CropCraft: Complete Structural Characterization of Crop Plants From Images](https://mlsanity.com/paper/2411.09693/) (2024)
- [Tree-Structured Shading Decomposition](https://mlsanity.com/paper/2309.07122/) (2023)
- [Single-view 3D reconstruction via inverse procedural modeling](https://mlsanity.com/paper/2310.13373/) (2023)
- [ProcGen3D: Learning Neural Procedural Graph Representations for Image-to-3D Reconstruction](https://mlsanity.com/paper/2511.07142/) (2025)
- [HeatMat: Simulation of City Material Impact on Urban Heat Island Effect](https://mlsanity.com/paper/2601.22796/) (2026)
- [Beyond Segmentation: Structurally Informed Facade Parsing from Imperfect Images](https://mlsanity.com/paper/2604.09260/) (2026)

## Abstract (arXiv)

In this paper, we address the following research problem: How can we generate a meaningful split grammar that explains a given facade layout? To evaluate if a grammar is meaningful, we propose a cost function based on the description length and minimize this cost using an approximate dynamic programming framework. Our evaluation indicates that our framework extracts meaningful split grammars that are competitive with those of expert users, while some users and all competing automatic solutions are less successful.