Light field (LF) cameras record both intensity and directions of light rays, and encode 3D
scenes into 4D LF images. Recently, many convolutional neural networks (CNNs) have …

Light Field (LF) cameras capture rich information in 4D LF images by recording both
intensity and angular directions, making it crucial to learn the inherent spatial-angular …

Light field (LF) cameras can record scenes from multiple perspectives, and thus introduce
beneficial angular information for image super-resolution (SR). However, it is challenging to …

Light field (LF) images acquired by hand-held devices usually suffer from low spatial
resolution as the limited sampling resources have to be shared with the angular dimension …

Light Field (LF) cameras are considered to have many potential applications since angular
and spatial information is captured simultaneously. However, the limited spatial resolution …

Exploiting spatial-angular correlation is crucial to light field (LF) image super-resolution
(SR), but is highly challenging due to its non-local property caused by the disparities among …

Light field cameras are considered to have many potential applications since angular and
spatial information is captured simultaneously. However, the limited spatial resolution has …

Light field images taken by plenoptic cameras often have a tradeoff between spatial and
angular resolutions. In this paper, we propose a novel spatial super-resolution approach for …

Light field (LF) photography is an emerging paradigm for capturing more immersive
representations of the real world. However, arising from the inherent tradeoff between the …

Most current super-resolution methods rely on low and high resolution image pairs to train a
network in a fully supervised manner. However, such image pairs are not available in real …