Matching cost construction is a key step in light field (LF) depth estimation, but was rarely
studied in the deep learning era. Recent deep learning-based LF depth estimation methods …

Light Field (LF) depth estimation is an important research direction in the area of computer
vision and computational photography, which aims to infer the depth information of different …

Light field (LF) depth estimation is a crucial basis for LF-related applications. Most existing
methods are based on the Lambertian assumption and cannot deal with non-Lambertian …

Since light field simultaneously records spatial information and angular information of light
rays, it is considered to be beneficial for many potential applications, and semantic …

Stereo vision is widely studied for depth information extraction. However, occlusion and
noise pose significant challenges to traditional methods due to failure in photo consistency …

Light field (LF) depth estimation plays a crucial role in many LF-based applications. Existing
LF depth estimation methods consider depth estimation as a regression problem, where a …

This paper presents the overview and rationale behind the Decoder-Side Depth Estimation
(DSDE) mode of the MPEG Immersive Video (MIV) standard, using the Geometry Absent …

Most existing light field (LF) disparity estimation algorithms focus on handling occlusion,
texture-less or other areas that harm LF structure to improve accuracy, while ignoring other …

Depth estimation using the Light Field (LF) technique is an essential task with a wide range
of practical applications. While mainstream approaches based on multi-view stereo …

Depth estimation is a fundamental issue in 4-D light field processing and analysis. Although
recent supervised learning-based light field depth estimation methods have significantly …