# Pano2CAD: Room Layout From A Single Panorama Image

arXiv: https://arxiv.org/abs/1609.09270 · HTML: https://mlsanity.com/paper/1609.09270/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Sep 2016.

## Built on by (most cited first, 20 of 20)

- [DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-based Optimization](https://mlsanity.com/paper/2108.10743/) (2021)
- [Pano2Room: Novel View Synthesis from a Single Indoor Panorama](https://mlsanity.com/paper/2408.11413/) (2024)
- [3D Room Layout Estimation from a Cubemap of Panorama Image via Deep Manhattan Hough Transform](https://mlsanity.com/paper/2207.09291/) (2022)
- [3D Scene Geometry Estimation from 360^circ Imagery: A Survey](https://mlsanity.com/paper/2401.09252/) (2024)
- [Indoor Panorama Planar 3D Reconstruction via Divide and Conquer](https://mlsanity.com/paper/2106.14166/) (2021)
- [OmniLayout: Room Layout Reconstruction from Indoor Spherical Panoramas](https://mlsanity.com/paper/2104.09403/) (2021)
- [360-DFPE: Leveraging Monocular 360-Layouts for Direct Floor Plan Estimation](https://mlsanity.com/paper/2112.06180/) (2021)
- [Single-Shot Cuboids: Geodesics-based End-to-end Manhattan Aligned Layout Estimation from Spherical Panoramas](https://mlsanity.com/paper/2102.03939/) (2021)
- [MVLayoutNet:3D layout reconstruction with multi-view panoramas](https://mlsanity.com/paper/2112.06133/) (2021)
- [Estimating Generic 3D Room Structures from 2D Annotations](https://mlsanity.com/paper/2306.09077/) (2023)
- [Semi-supervised reference-based sketch extraction using a contrastive learning framework](https://mlsanity.com/paper/2407.14026/) (2024)
- [Walk2Map: Extracting Floor Plans from Indoor Walk Trajectories](https://mlsanity.com/paper/2103.00262/) (2021)
- [360-MLC: Multi-view Layout Consistency for Self-training and Hyper-parameter Tuning](https://mlsanity.com/paper/2210.12935/) (2022)
- [Self-training Room Layout Estimation via Geometry-aware Ray-casting](https://mlsanity.com/paper/2407.15041/) (2024)
- [CAGE: Continuity-Aware edGE Network Unlocks Robust Floorplan Reconstruction](https://mlsanity.com/paper/2509.15459/) (2025)
- [Monocular Spherical Depth Estimation with Explicitly Connected Weak Layout Cues](https://mlsanity.com/paper/2206.11358/) (2022)
- [GRIHA: Synthesizing 2-Dimensional Building Layouts from Images Captured using a Smart Phone](https://mlsanity.com/paper/2103.08297/) (2021)
- [PanoViT: Vision Transformer for Room Layout Estimation from a Single Panoramic Image](https://mlsanity.com/paper/2212.12156/) (2022)
- [PanoTPS-Net: Panoramic Room Layout Estimation via Thin Plate Spline Transformation](https://mlsanity.com/paper/2510.11992/) (2025)
- [FastPano3D: Feed-Forward Indoor Panoramic 3D Reconstruction from a Single Image](https://mlsanity.com/paper/2606.30352/) (2026)

## Abstract (arXiv)

This paper presents a method of estimating the geometry of a room and the 3D pose of objects from a single 360-degree panorama image. Assuming Manhattan World geometry, we formulate the task as a Bayesian inference problem in which we estimate positions and orientations of walls and objects. The method combines surface normal estimation, 2D object detection and 3D object pose estimation. Quantitative results are presented on a dataset of synthetically generated 3D rooms containing objects, as well as on a subset of hand-labeled images from the public SUN360 dataset.