# GRIHA: Synthesizing 2-Dimensional Building Layouts from Images Captured using a Smart Phone

arXiv: https://arxiv.org/abs/2103.08297 · HTML: https://mlsanity.com/paper/2103.08297/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 33 references that are in the map.
- First posted on arXiv 15 Mar 2021.

## Builds on (most cited first, 10 of 10)

- [Atlas: End-to-End 3D Scene Reconstruction from Posed Images](https://mlsanity.com/paper/2003.10432/) (2020)
- [The VIA Annotation Software for Images, Audio and Video](https://mlsanity.com/paper/1904.10699/) (2019)
- [High Quality Monocular Depth Estimation via Transfer Learning](https://mlsanity.com/paper/1812.11941/) (2018)
- [HorizonNet: Learning Room Layout with 1D Representation and Pano Stretch Data Augmentation](https://mlsanity.com/paper/1901.03861/) (2019)
- [LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image](https://mlsanity.com/paper/1803.08999/) (2018)
- [Pano2CAD: Room Layout From A Single Panorama Image](https://mlsanity.com/paper/1609.09270/) (2016)
- [Layouts from Panoramic Images with Geometry and Deep Learning](https://mlsanity.com/paper/1806.08294/) (2018)
- [Edge-Semantic Learning Strategy for Layout Estimation in Indoor Environment](https://mlsanity.com/paper/1901.00621/) (2019)
- [Flat2Layout: Flat Representation for Estimating Layout of General Room Types](https://mlsanity.com/paper/1905.12571/) (2019)
- [Scan2Plan: Efficient Floorplan Generation from 3D Scans of Indoor Scenes](https://mlsanity.com/paper/2003.07356/) (2020)

## Abstract (arXiv)

Reconstructing an indoor scene and generating a layout/floor plan in 3D or 2D is a widely known problem. Quite a few algorithms have been proposed in the literature recently. However, most existing methods either use RGB-D images, thus requiring a depth camera, or depending on panoramic photos, assuming that there is little to no occlusion in the rooms. In this work, we proposed GRIHA (Generating Room Interior of a House using ARCore), a framework for generating a layout using an RGB image captured using a simple mobile phone camera. We take advantage of Simultaneous Localization and Mapping (SLAM) to assess the 3D transformations required for layout generation. SLAM technology is built-in in recent mobile libraries such as ARCore by Google. Hence, the proposed method is fast and efficient. It gives the user freedom to generate layout by merely taking a few conventional photos, rather than relying on specialized depth hardware or occlusion-free panoramic images. We have compared GRIHA with other existing methods and obtained superior results. Also, the system is tested on multiple hardware platforms to test the dependency and efficiency.