Automatic Rendering of Building Floor Plan Images from Textual Descriptions in English

TL;DR

This paper presents the first automatic method to generate 2D building floor plan images from natural language descriptions, enabling visual representation of interior structures based on textual input.

Contribution

It introduces a novel approach for rendering building floor plans directly from English descriptions, filling a gap in document image synthesis from natural language.

Findings

Successfully generated realistic floor plans from textual descriptions

Performed experiments on benchmark datasets demonstrating effectiveness

Achieved promising results in automatic floor plan rendering

Abstract

Human beings understand natural language description and could able to imagine a corresponding visual for the same. For example, given a description of the interior of a house, we could imagine its structure and arrangements of furniture. Automatic synthesis of real-world images from text descriptions has been explored in the computer vision community. However, there is no such attempt in the area of document images, like floor plans. Floor plan synthesis from sketches, as well as data-driven models, were proposed earlier. Ours is the first attempt to render building floor plan images from textual description automatically. Here, the input is a natural language description of the internal structure and furniture arrangements within a house, and the output is the 2D floor plan image of the same. We have experimented on publicly available benchmark floor plan datasets. We were able to render realistic synthesized floor plan images from the description written in English.