As an essential component for many autonomous driving and robotic activities such as ego-
motion estimation, obstacle avoidance and scene understanding, monocular depth …

We propose a novel algorithm for monocular depth estimation using relative depth maps.
First, using a convolutional neural network, we estimate relative depths between pairs of …

An algorithm to combine multiple loss terms adaptively for training a monocular depth
estimator is proposed in this work. We construct a loss function space containing tens of …

We present the design and implementation of ParkMaster, a system that leverages the
ubiquitous smartphone to help drivers find parking spaces in the urban environment …

This research work focuses on a widespread interpretation for the operation of depth
estimation using machine learning (ML) algorithms and computer vision. Depth estimation …

The moving object recognition system includes: a camera that is installed in a vehicle and
captures continuous single-view images; a moving object detecting unit that detects a …

Computer stereo vision is an important technique for robotic navigation and other mobile
scenarios where depth perception is needed, but it usually requires two cameras with a …

An autonomous vehicle is a demanding application for our daily life. Such vehicle requires
to detect other vehicles on the road. Given the sequences of images, the algorithms need to …

Depth estimation from a single RGB image is a challenging task. It is ill-posed since a single
2D image may correspond to various 3D scenes at different scales. On the other hand …

Depth estimation based on a single RGB image (aka monocular depth estimation) is a
challenging task, with applications in robotics, autonomous vehicles, and other areas. With …