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 …

In recent years, monocular depth estimation is applied to understand the surrounding 3D
environment and has made great progress. However, there is an ill-posed problem on how …

Depth estimation is an essential component in computer vision systems for achieving 3D
scene understanding. Efficient and accurate depth map estimation has numerous …

Monocular depth estimation is an extensively studied computer vision problem with a vast
variety of applications. Deep learning-based methods have demonstrated promise for both …

Monocular depth estimation has drawn widespread attention from the vision community due
to its broad applications. In this paper, we propose a novel physics (geometry)-driven deep …

Self-supervised monocular depth estimation has achieved encouraging performance
recently. A consensus is that high-resolution inputs often yield better results. However, we …

In computer vision, monocular depth estimation is the problem of obtaining a high-quality
depth map from a two-dimensional image. This map provides information on three …

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 …

Understanding 3-D scene geometry from videos is a fundamental topic in visual perception.
In this article, we propose an unsupervised monocular depth and camera motion estimation …

Predicting a high quality depth map from a single image is a challenging task, because it
exists infinite possibility to project a 2D scene to the corresponding 3D scene. Recently …