Room Layout Estimation
17 papers with code • 1 benchmarks • 4 datasets
SUN RGB-D
Structured3D
Rent3D
Latest papers with no code
No More Ambiguity in 360° Room Layout via Bi-Layout Estimation
A unique property of our Bi-Layout model is its ability to inherently detect ambiguous regions by comparing the two predictions.
iBARLE: imBalance-Aware Room Layout Estimation
iBARLE consists of (1) Appearance Variation Generation (AVG) module, which promotes visual appearance domain generalization, (2) Complex Structure Mix-up (CSMix) module, which enhances generalizability w. r. t.
Shape-Net: Room Layout Estimation from Panoramic Images Robust to Occlusion using Knowledge Distillation with 3D Shapes as Additional Inputs
It is possible to obtain 3D shape information of rooms as drawings of buildings and coordinates of corners from image datasets, thus we propose providing both 2D panoramic and 3D information to a model to effectively deal with occlusion.
U2RLE: Uncertainty-Guided 2-Stage Room Layout Estimation
While the existing deep learning-based room layout estimation techniques demonstrate good overall accuracy, they are less effective for distant floor-wall boundary.
PanoViT: Vision Transformer for Room Layout Estimation from a Single Panoramic Image
In this paper, we propose PanoViT, a panorama vision transformer to estimate the room layout from a single panoramic image.
Monocular Spherical Depth Estimation with Explicitly Connected Weak Layout Cues
Spherical cameras capture scenes in a holistic manner and have been used for room layout estimation.
Self-supervised 360$^{\circ}$ Room Layout Estimation
We present the first self-supervised method to train panoramic room layout estimation models without any labeled data.
PSMNet: Position-aware Stereo Merging Network for Room Layout Estimation
In this paper, we propose a new deep learning-based method for estimating room layout given a pair of 360 panoramas.
Transferable End-to-end Room Layout Estimation via Implicit Encoding
Here we propose an end-to-end method that directly predicts parametric layouts from an input panorama image.
MINERVAS: Massive INterior EnviRonments VirtuAl Synthesis
With the rapid development of data-driven techniques, data has played an essential role in various computer vision tasks.
