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 …

Deep learning provides a new avenue for light field super-resolution (SR). However, the
domain gap caused by drastically different light field acquisition conditions poses a main …

Visual measurement methods are extensively used in various fields, such as aerospace,
biomedicine, agricultural production, and social life, owing to their advantages of high …

Photon-efficient imaging has enabled a number of applications relying on single-photon
sensors that can capture a 3D image with as few as one photon per pixel. In practice …

Background objects occluded in some views of a light field (LF) camera can be seen by
other views. Consequently, occluded surfaces are possible to be reconstructed from LF …

The disparity information reflects pixel-wise inter-view correlations among sub-aperture
images (SAIs) of a light field (LF) image. Existing CNN-based methods for LF spatial super …

Photon-efficient imaging, which captures 3D images with single-photon sensors, has
enabled a wide range of applications. However, two major challenges limit the …

This article proposes a zero-shot learning-based framework for light field depth estimation,
which learns an end-to-end mapping solely from an input light field to the corresponding …

Although learning-based light field disparity estimation has achieved great progress in the
most recent years, the performance of unsupervised light field learning is still hindered by …