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 …

Estimating the accurate depth from a single image is challenging since it is inherently
ambiguous and ill-posed. While recent works design increasingly complicated and powerful …

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 …

Panoramic images with their 360deg directional view encompass exhaustive information
about the surrounding space, providing a rich foundation for scene understanding. To unfold …

This paper addresses the task of estimating the light arriving from all directions to a 3D point
observed at a selected pixel in an RGB image. This task is challenging because it requires …

We present HoHoNet, a versatile and efficient framework for holistic understanding of an
indoor 360-degree panorama using a Latent Horizontal Feature (LHFeat). The compact …

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 …

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 …

We introduce a method to convert stereo 360^ ∘ (omnidirectional stereo) imagery into a
layered, multi-sphere image representation for six degree-of-freedom (6DoF) rendering …