Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

Nowadays, 360° video/image has been increasingly popular and drawn great attention. The
spherical viewing range of 360° video/image accounts for huge data, which pose the …

Due to the lack of camera parameter information for in-the-wild images, existing 3D human
pose and shape (HPS) estimation methods make several simplifying assumptions: weak …

Access to large, diverse RGB-D datasets is critical for training RGB-D scene understanding
algorithms. However, existing datasets still cover only a limited number of views or a …

Despite significant progress in monocular depth estimation in the wild, recent state-of-the-art
methods cannot be used to recover accurate 3D scene shape due to an unknown depth shift …

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 propose an automatic method to infer high dynamic range illumination from a single,
limited field-of-view, low dynamic range photograph of an indoor scene. In contrast to …

Recovering the 3D shape of an object from single or multiple images with deep neural
networks has been attracting increasing attention in the past few years. Mainstream works …

We introduce a novel self-supervised pretext task for learning representations from audio-
visual content. Prior work on audio-visual representation learning leverages …

Recently, there has been growing interest in developing learning-based methods to detect
and utilize salient semi-global or global structures, such as junctions, lines, planes, cuboids …