3 papers
cs.CV2023
iBARLE: imBalance-Aware Room Layout Estimation
Taotao Jing, Lichen Wang, Naji Khosravan +4
Room layout estimation predicts layouts from a single panorama. It requires datasets with large-scale and diverse room shapes to train the models. However, there are significant im…
cs.CV2023
U2RLE: Uncertainty-Guided 2-Stage Room Layout Estimation
Pooya Fayyazsanavi, Zhiqiang Wan, Will Hutchcroft +4
While the existing deep learning-based room layout estimation techniques demonstrate good overall accuracy, they are less effective for distant floor-wall boundary. To tackle this…
cs.CV2022
PSMNet: Position-aware Stereo Merging Network for Room Layout Estimation
Haiyan Wang, Will Hutchcroft, Yuguang Li +4
In this paper, we propose a new deep learning-based method for estimating room layout given a pair of 360 panoramas. Our system, called Position-aware Stereo Merging Network or PSM…