Despite significant research focus on 3D scene capture systems, numerous unresolved
challenges remain in relation to achieving full coverage scene depth estimation which is the …

Depth maps are crucial for many visual applications, where they represent the positioning
information of the objects in a three‐dimensional scene. Usually, depth maps can be …

Facial emotion recognition extracts the human emotions from the images and videos. As
such, it requires an algorithm to understand and model the relationships between faces and …

Image ALU is a special type of ALU exclusively designed to perform arithmetic and logical
operation on Image only. This Image ALU design is able to perform 14 operations. In this …

Depth maps taken by the low cost Kinect sensor are often noisy and incomplete. Thus, post-
processing for obtaining reliable depth maps is necessary for advanced image and video …

Depth maps acquired by either physical sensors or learning methods are often seriously
distorted due to boundary distortion problems, including missing, fake, and misaligned …

Compared to the color images, their associated depth images captured by the RGB-D
sensors are typically with lower resolution. The task of depth map super-resolution (SR) …

3D depth cameras have become more and more popular in recent years. However, depth
maps captured by these cameras can hardly be used in 3D reconstruction directly because …

Depth maps generally suffer from large erroneous areas even in public RGB-Depth
datasets. Existing learning-based depth recovery methods are limited by insufficient high …

Image acquisition is generally susceptible to poor environmental conditions such as fog,
smog, haze, etc. However, designing an efficient image dehazing technique is still an ill …