Though semantic segmentation has been heavily explored in vision literat...
This work addresses the task of overhead image segmentation when auxilia...
Modern cameras are equipped with a wide array of sensors that enable
rec...
Most pictures shared online are accompanied by a temporal context (i.e.,...
The appearance of the world varies dramatically not only from place to p...
Estimating camera pose from a single image is a fundamental problem in
c...
Our goal is to use overhead imagery to understand patterns in traffic fl...
Artifacts in imagery captured by remote sensing, such as clouds, snow, a...
Roadway free-flow speed captures the typical vehicle speed in low traffi...
We propose to implicitly learn to extract geo-temporal image features, w...
This paper addresses the task of road safety assessment. An emerging app...
In this work, we propose a cross-view learning approach, in which images...
We propose a novel convolutional neural network architecture for estimat...
While natural beauty is often considered a subjective property of images...
We introduce a novel strategy for learning to extract semantically meani...
We propose a novel method for detecting horizontal vanishing points and ...
The horizon line is an important contextual attribute for a wide variety...
We propose to use deep convolutional neural networks to address the prob...