Stereo matching is one of the longest-standing problems in computer vision with close to 40
years of studies and research. Throughout the years the paradigm has shifted from local …

Modern image inpainting systems, despite the significant progress, often struggle with large
missing areas, complex geometric structures, and high-resolution images. We find that one …

Abstract Visual Place Recognition is a challenging task for robotics and autonomous
systems, which must deal with the twin problems of appearance and viewpoint change in an …

Estimating the depth of the 3D world from 2D images is a classic and important issue in
computer vision, which has been widely studied for decades. With the remarkable effect of …

Visual place recognition is a challenging task for applications such as autonomous driving
navigation and mobile robot localization. Distracting elements presenting in complex scenes …

Abstract Recently, several Space-Time Memory based networks have shown that the object
cues (eg video frames as well as the segmented object masks) from the past frames are …

Recent advances in 3D perception have shown impressive progress in understanding
geometric structures of 3D shapes and even scenes. Inspired by these advances in …

Land cover classification of remote sensing images is a challenging task due to limited
amounts of annotated data, highly imbalanced classes, frequent incorrect pixel-level …

Tasks that involve high-resolution dense prediction require a modeling of both local and
global patterns in a large input field. Although the local and global structures often depend …

In the current monocular depth research, the dominant approach is to employ unsupervised
training on large datasets, driven by warped photometric consistency. Such approaches lack …