Light field imaging has emerged as a technology allowing to capture richer visual
information from our world. As opposed to traditional photography, which captures a 2D …

In computer vision communities such as stereo, optical flow, or visual tracking, commonly
accepted and widely used benchmarks have enabled objective comparison and boosted …

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 …

Light field cameras capture both the spatial and the angular properties of light rays in space.
Due to its property, one can compute the depth from light fields in uncontrolled lighting …

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 …

Depth estimation is a fundamental problem for light field photography applications.
Numerous methods have been proposed in recent years, which either focus on crafting cost …

This paper presents the results of the depth estimation challenge for dense light fields, which
took place at the second workshop on Light Fields for Computer Vision (LF4CV) in …

One of the core applications of light field imaging is depth estimation. To acquire a depth
map, existing approaches apply a single photo-consistency measure to an entire light field …

Epipolar plane images (EPIs) contain special linear structures that reflect the disparity of a
3D point and are widely used in light field depth estimation. However, previous EPI-based …

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 …