Deep Floor Plan Recognition Using a Multi-Task Network with Room-Boundary-Guided Attention [article]

Zhiliang Zeng and Xianzhi Li and Ying Kin Yu and Chi-Wing Fu
2019 arXiv   pre-print
This paper presents a new approach to recognize elements in floor plan layouts. Besides walls and rooms, we aim to recognize diverse floor plan elements, such as doors, windows and different types of rooms, in the floor layouts. To this end, we model a hierarchy of floor plan elements and design a deep multi-task neural network with two tasks: one to learn to predict room-boundary elements, and the other to predict rooms with types. More importantly, we formulate the room-boundary-guided
more » ... on mechanism in our spatial contextual module to carefully take room-boundary features into account to enhance the room-type predictions. Furthermore, we design a cross-and-within-task weighted loss to balance the multi-label tasks and prepare two new datasets for floor plan recognition. Experimental results demonstrate the superiority and effectiveness of our network over the state-of-the-art methods.
arXiv:1908.11025v1 fatcat:3a5jphe4sbdghgfdkrpkzdtsru