Papers › LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image

LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image

23 Mar 2018CVPR 2018 6arXiv:1803.08999archive 2025-07-28

Chuhang Zou, Alex Colburn, Qi Shan, Derek Hoiem

We propose an algorithm to predict room layout from a single image that generalizes across panoramas and perspective images, cuboid layouts and more general layouts (e.g. L-shape room). Our method operates directly on the panoramic image, rather than decomposing into perspective images as do recent works. Our network architecture is similar to that of RoomNet, but we show improvements due to aligning the image based on vanishing points, predicting multiple layout elements (corners, boundaries, size and translation), and fitting a constrained Manhattan layout to the resulting predictions. Our method compares well in speed and accuracy to other existing work on panoramas, achieves among the best accuracy for perspective images, and can handle both cuboid-shaped and more general Manhattan layouts.

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Tasks

3D Room Layouts From A Single RGB PanoramaTranslation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Room Layouts From A Single RGB Panorama PanoContext LayoutNet 3DIoU 74.48 #7 of 7 Archive leaderboard report
3D Room Layouts From A Single RGB Panorama Realtor360 LayoutNet 3DIoU 62.77% #2 of 2 Archive leaderboard report
3D Room Layouts From A Single RGB Panorama Stanford2D3D Panoramic LayoutNet 3DIoU 76.33 #9 of 9 Archive leaderboard report
3D Room Layouts From A Single RGB Panorama Stanford2D3D Panoramic LayoutNet Corner Error 1.04 #9 of 9 Archive leaderboard report
3D Room Layouts From A Single RGB Panorama Stanford2D3D Panoramic LayoutNet Pixel Error 2.7 #9 of 9 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

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