Abstract Three-dimensional (3D) object recognition is widely used in automated driving,
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …

Multi-view stereo infers the 3D geometry from a set of images captured from several known
positions and viewpoints. It is one of the most important components of 3D reconstruction …

Three-dimensional models are widely used in the fields of multimedia, computer graphics,
virtual reality, entertainment, design, and manufacturing because of the rich information that …

Researchers and engineers have increasingly used Deep Learning (DL) for a variety of
Remote Sensing (RS) tasks. However, data from local observations or via ground truth is …

Images captured from different viewpoints or devices have often exhibited significant
geometric and photometric differences due to factors such as environmental variations …

Semantic segmentation is referred to as a process of linking each pixel in an image to a
class label. With this pragmatic technique, it is possible to recognize different objects in an …

Multi-viewpoint image stitching aims to stitch images taken from different viewpoints into
pictures with a broader field of view. The stitched images are subject to artifacts, geometric …

Recently, there has been growing attention on an end-to-end deep learning-based stitching
model. However, the most challenging point in deep learning-based stitching is to obtain …

Deep learning approaches have significantly contributed to recent progress in stereo
matching. These deep stereo matching methods are usually based on supervised training …

In stereo matching tasks, the matching effect is often very poor when the texture of the region
is weak or repeated. To solve this problem, an improved Graph Cut stereo matching …