With the rapid development of high-speed communication and artificial intelligence
technologies, human perception of real-world scenes is no longer limited to the use of small …

Indoor environment model reconstruction has emerged as a significant and challenging task
in terms of the provision of a semantically rich and geometrically accurate indoor model …

A well-known challenge in applying deep-learning methods to omnidirectional images is
spherical distortion. In dense regression tasks such as depth estimation, where structural …

We present a new approach to the problem of estimating the 3D room layout from a single
panoramic image. We represent room layout as three 1D vectors that encode, at each image …

Abstract 360deg cameras can capture complete environments in a single shot, which makes
360deg imagery alluring in many computer vision tasks. However, monocular depth …

Learning depth from spherical panoramas is becoming a popular research topic because a
panorama has a full field-of-view of the environment and provides a relatively complete …

Learning based approaches for depth perception are limited by the availability of clean
training data. This has led to the utilization of view synthesis as an indirect objective for …

Depth estimation is a crucial step for 3D reconstruction with panorama images in recent
years. Panorama images maintain the complete spatial information but introduce distortion …

This article provides a comprehensive survey on pioneer and state-of-the-art 3D scene
geometry estimation methodologies based on single, two, or multiple images captured …

We introduce a novel end-to-end approach to predict a 3D room layout from a single
panoramic image. Compared to recent state-of-the-art works, our method is not limited to …