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 …

We present a machine learning algorithm that takes as input a 2D RGB image and
synthesizes a 4D RGBD light field (color and depth of the scene in each ray direction). For …

Light field imaging is an emerging technology in computational photography areas. Based
on innovative designs of the imaging model and the optical path, light field cameras not only …

Superpixel segmentation of 2D image has been widely used in many computer vision tasks.
However, limited to the Gaussian imaging principle, there is not a thorough segmentation …

Shape is one of the fundamental visual features in the content-based image retrieval (CBIR)
paradigm. Numerous shape descriptors have been proposed in the literature. These can be …

We study the problem of deblurring light fields of general 3D scenes captured under 3D
camera motion and present both theoretical and practical contributions. By analyzing the …

Efficient and accurate segmentation of full 4D light fields is an important task in computer
vision and computer graphics. The massive volume and the redundancy of light fields make …

Previous 2D saliency detection methods extract salient cues from a single view and directly
predict the expected results. Both traditional and deep-learning-based 2D methods do not …

This paper is the first to review the scene flow estimation field, which analyzes and
compares methods, technical challenges, evaluation methodologies and performance of …

Depth estimation on light field images has been well researched on synthetic datasets.
However, existing methods often fail on real-world light field images because of the real …