We focus on the task of soundscape mapping, which involves predicting th...
We introduce a novel training strategy for stereo matching and optical f...
We propose a novel weakly supervised approach for creating maps using
fr...
The monetary value of a given piece of real estate, a parcel, is often
r...
Many problems can be viewed as forms of geospatial search aided by aeria...
As unconventional sources of geo-information, massive imagery and text
m...
There have been several post-hoc explanation approaches developed to exp...
This work addresses the task of overhead image segmentation when auxilia...
Most research on domain adaptation has focused on the purely unsupervise...
Constructing a point cloud for a large geographic region, such as a stat...
In the last years we have witnessed the fields of geosciences and remote...
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...
Most galaxies in the nearby Universe are gravitationally bound to a clus...
We propose to apply a 2D CNN architecture to 3D MRI image Alzheimer's di...
When training deep neural networks for medical image classification,
obt...
Recent works have shown that deep neural networks can achieve super-huma...
Artifacts in imagery captured by remote sensing, such as clouds, snow, a...
We introduce a deep learning approach to perform fine-grained population...
Roadway free-flow speed captures the typical vehicle speed in low traffi...
Generalization is one of the key challenges in the clinical validation a...
Breast cancer is the malignant tumor that causes the highest number of c...
Automated methods for breast cancer detection have focused on 2D mammogr...
Despite remarkable performance across a broad range of tasks, neural net...
We propose to implicitly learn to extract geo-temporal image features, w...
Looking at the world from above, it is possible to estimate many propert...
We propose an automated method to estimate a road segment's free-flow sp...
This paper addresses the task of road safety assessment. An emerging app...
We propose a neural network component, the regional aggregation layer, t...
In this work, we propose a cross-view learning approach, in which images...
Given a single RGB image of a complex outdoor road scene in the perspect...
We propose a novel convolutional neural network architecture for estimat...
Image geolocalization, inferring the geographic location of an image, is...
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...
Recovering shadows is an important step for many vision algorithms. Curr...