长方体
计算机科学
图形
计算
推论
代表(政治)
算法
人工智能
理论计算机科学
数学
几何学
政治
政治学
法学
作者
Hui Yao,Jun Miao,Yilin Zheng,Guoxiang Zhang,Jun Chu
标识
DOI:10.1016/j.jvcir.2023.103963
摘要
Room layout estimation aims to predict the spatial structure of a room from a single image. Most existing methods relying on 2D cues are suitable for cuboid rooms, but non-cuboid rooms. 3D layout estimation methods can reconstruct 3D models of general rooms, but they are trained with depth information on high collection costs, consume large computation resources, and run slowly. This paper considers an undirected graph representation method of the general room layouts, which includes cuboid and non-cuboid rooms consisting of a single ceiling, a single floor, and multiple walls. To this end, we first predict the positions of the layout vertices and then use the network automatically learn the connection relationship between the vertices. The final layout is obtained through a simple layout inference post-processing algorithm. The experimental results both on cuboid and non-cuboid datasets validate the effectiveness and efficiency of our method. The code is available at https://github.com/Hui-Yao/2D-graph-layout-estimation.
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