Acquiring scene depth information remains a crucial step in most autonomous navigation
applications, enabling advanced features such as obstacle avoidance and SLAM. In many …

The Unmanned Aerial Vehicles (UAVs) have gained increasing attention recently, and depth
estimation is one of the essential tasks for the safe operation of UAVs, especially for drones …

Estimating the distance to objects is crucial for autonomous vehicles when using depth
sensors is not possible. In this case, the distance has to be estimated from on-board …

Environment perception by computing the depth is a key task for unmanned aerial vehicle
(UAV) type systems. Due to the limited load they can carry, most drones are equipped with a …

Monocular depth estimation is very challenging because clues to the exact depth are
incomplete in a single RGB image. To overcome the limitation, deep neural networks rely on …

Monocular depth estimation has gained increasing attention in recent years, and various
techniques have been proposed to tackle this problem. In this work, we aim to provide a …

There has been tremendous research progress in estimating the depth of a scene from a
monocular camera image. Existing methods for single-image depth prediction are …

Recently, neural networks have shown promising results in estimating depth from a single
image. A large amount of per-pixel ground truth depth data is required to train the neural …

Depth estimation is one of the most important tasks in scene understanding. In the existing
joint self-supervised learning approaches of depth-pose estimation, depth estimation and …

Monocular depth estimation, which plays a key role in understanding 3D scene geometry, is
fundamentally an ill-posed problem. Existing methods based on deep convolutional neural …