Depth estimation is a classic task in computer vision, which is of great significance for many
applications such as augmented reality, target tracking and autonomous driving. Traditional …

In this work, we present a new multi-view depth estimation method that utilizes both
conventional SfM reconstruction and learning-based priors over the recently proposed …

We present a novel framework named NeuralRecon for real-time 3D scene reconstruction
from a monocular video. Unlike previous methods that estimate single-view depth maps …

We present an algorithm for reconstructing dense, geometrically consistent depth for all
pixels in a monocular video. We leverage a conventional structure-from-motion …

We present an algorithm for estimating consistent dense depth maps and camera poses
from a monocular video. We integrate a learning-based depth prior, in the form of a …

The integration of augmented reality and drones allows past and future landscapes to be
visualized from an aerial perspective. However, these visualizations still suffer from the …

Mobile devices with passive depth sensing capabilities are ubiquitous, and recently active
depth sensors have become available on some tablets and AR/VR devices. Although real …

We present a real-time monocular 3D reconstruction system on a mobile phone, called
Mobile3DRecon. Using an embedded monocular camera, our system provides an online …

Visual localization and mapping algorithms attempt to estimate, from images, geometrical
models that explain ego motion and the positions of objects in a real scene. The success of …

Virtual reality headsets are becoming increasingly popular, yet it remains difficult for casual
users to capture immersive 360° VR panoramas. State-of-the-art approaches require …