Compared with external-supervised learning-based (ESLB) methods, self-supervised
learning-based (SSLB) methods can overcome the domain gap problem caused by different …

In recent years, point clouds have become increasingly popular for representing three-
dimensional (3D) visual objects and scenes. To efficiently store and transmit point clouds …

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 …

We propose a high-quality, three-dimensional display system based on a simplified light
field image acquisition method, and a custom-trained full-connected deep neural network is …

Depth estimation for light field images is crucial in light field applications such as image-
based rendering and refocusing. Previous learning-based methods com bining neural …

The importance of three-dimensional (3D) point cloud technologies in the field of agriculture
environmental research has increased in recent years. Obtaining dense and accurate 3D …

Point clouds have been recently used in applications involving real-time capture and
rendering of 3D objects. In a point cloud, for practical reasons, each point or voxel is usually …

The light field (LF) imaging technique can capture 3D scene information in 4D by recording
both 2D intensity and 2D direction of incoming light rays. Due to this capability, LF has …

This paper proposes an algorithm for lossy compression of unfocused light field images. The
raw light field is preprocessed by demosaicing, devignetting and slicing of the raw lenset …

A point cloud acquired through a Light Detection And Ranging (LiDAR) sensor can be
illustrated as a continuous frame with a time axis. Since the frame-by-frame point cloud has …