2 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
High-Resolution Depth Estimation for 360-degree Panoramas through Perspective and Panoramic Depth Images Registration
Chi-Han Peng, Jiayao Zhang
We propose a novel approach to compute high-resolution (2048x1024 and higher) depths for panoramas that is significantly faster and qualitatively and qualitatively more accurate th…
GPR-Net: Multi-view Layout Estimation via a Geometry-aware Panorama Registration Network
Jheng-Wei Su, Chi-Han Peng, Peter Wonka +1
Reconstructing 3D layouts from multiple panoramas has received increasing attention recently as estimating a complete layout of a large-scale and complex room from a…
Manhattan Room Layout Reconstruction from a Single 360 image: A Comparative Study of State-of-the-art Methods
Chuhang Zou, Jheng-Wei Su, Chi-Han Peng +5
Recent approaches for predicting layouts from 360 panoramas produce excellent results. These approaches build on a common framework consisting of three steps: a pre-processing step…
DuLa-Net: A Dual-Projection Network for Estimating Room Layouts from a Single RGB Panorama
Shang-Ta Yang, Fu-En Wang, Chi-Han Peng +3
We present a deep learning framework, called DuLa-Net, to predict Manhattan-world 3D room layouts from a single RGB panorama. To achieve better prediction accuracy, our method leve…