activity
20152024
most citedDepthTransfer: Depth Extraction from Video Using Non-parametric Sampling

501 citations · 832 across the 16 of their papers we have counts for

collaborators

19 papers

cs.CV2024

SALVe: Semantic Alignment Verification for Floorplan Reconstruction from Sparse Panoramas

John Lambert, Yuguang Li, Ivaylo Boyadzhiev +6

We propose a new system for automatic 2D floorplan reconstruction that is enabled by SALVe, our novel pairwise learned alignment verifier. The inputs to our system are sparsely loc…

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

Graph-CoVis: GNN-based Multi-view Panorama Global Pose Estimation

Negar Nejatishahidin, Will Hutchcroft, Manjunath Narayana +5

In this paper, we address the problem of wide-baseline camera pose estimation from a group of 360 panoramas under upright-camera assumption. Recent work has demonstrated th…

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.GR2022

Semantically Supervised Appearance Decomposition for Virtual Staging from a Single Panorama

Tiancheng Zhi, Bowei Chen, Ivaylo Boyadzhiev +3

We describe a novel approach to decompose a single panorama of an empty indoor environment into four appearance components: specular, direct sunlight, diffuse and diffuse ambient w…

cs.CV2022★ 6 cited

Generating Topological Structure of Floorplans from Room Attributes

Yin Yu, Hutchcroft Will, Khosravan Naji +3

Analysis of indoor spaces requires topological information. In this paper, we propose to extract topological information from room attributes using what we call Iterative and adapt…