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arXiv · 2210.17411

Offset-Guided Attention Network for Room-Level Aware Floor Plan Segmentation

Zhangyu Wang·Ningyuan Sun
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Abstract

Recognition of floor plans has been a challenging and popular task. Despite that many recent approaches have been proposed for this task, they typically fail to make the room-level unified prediction. Specifically, multiple semantic categories can be assigned in a single room, which seriously limits their visual quality and applicability. In this paper, we propose a novel approach to recognize the floor plan layouts with a newly proposed Offset-Guided Attention mechanism to improve the semantic consistency within a room. In addition, we present a Feature Fusion Attention module that leverages the channel-wise attention to encourage the consistency of the room, wall, and door predictions, further enhancing the room-level semantic consistency. Experimental results manifest our approach is able to improve the room-level semantic consistency and outperforms the existing works both qualitatively and quantitatively.

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Zhangyu Wang, Ningyuan Sun. 2022-10-22. Offset-Guided Attention Network for Room-Level Aware Floor Plan Segmentation. https://arxiv.org/abs/2210.17411

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