Depth completion aims at predicting dense pixel-wise depth from an extremely sparse map
captured from a depth sensor, eg, LiDARs. It plays an essential role in various applications …

Guided depth map super-resolution (GDSR), which aims to reconstruct a high-resolution
depth map from a low-resolution observation with the help of a paired high-resolution color …

Depth image denoising is increasingly becoming the hot research topic nowadays, because
it reflects the three-dimensional scene and can be applied in various fields of computer …

Depth completion, the technique of estimating a dense depth image from sparse depth
measurements, has a variety of applications in robotics and autonomous driving. However …

We propose a method for converting a single RGB-D input image into a 3D photo, ie, a multi-
layer representation for novel view synthesis that contains hallucinated color and depth …

Guided depth map super-resolution (GDSR), as a hot topic in multi-modal image processing,
aims to upsample low-resolution (LR) depth maps with additional information involved in …

Guided depth super-resolution (GDSR) is an essential topic in multi-modal image
processing, which reconstructs high-resolution (HR) depth maps from low-resolution ones …

Low-rank recovery models have shown potential for salient object detection, where a matrix
is decomposed into a low-rank matrix representing image background and a sparse matrix …

Joint image filters can leverage the guidance image as a prior and transfer the structural
details from the guidance image to the target image for suppressing noise or enhancing …

Most existing image dehazing methods tend to boost local image contrast for regions with
heavy haze. Without special treatment, these methods may significantly amplify existing …