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Wide-Area Image Geolocalization with Aerial Reference Imagery
We propose to use deep convolutional neural networks to address the problem of cross-view image geolocalization, in which the geolocation of a ground-level query image is estimated by matching toExpand
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Predicting Ground-Level Scene Layout from Aerial Imagery
We introduce a novel strategy for learning to extract semantically meaningful features from aerial imagery. Instead of manually labeling the aerial imagery, we propose to predict (noisy) semanticExpand
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Horizon Lines in the Wild
The horizon line is an important contextual attribute for a wide variety of image understanding tasks. As such, many methods have been proposed to estimate its location from a single image. TheseExpand
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Detecting Vanishing Points Using Global Image Context in a Non-ManhattanWorld
We propose a novel method for detecting horizontal vanishing points and the zenith vanishing point in man-made environments. The dominant trend in existing methods is to first find candidateExpand
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Sky segmentation in the wild: An empirical study
Automatically determining which pixels in an image view the sky, the problem of sky segmentation, is a critical preprocessing step for a wide variety of outdoor image interpretation problems,Expand
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A Unified Model for Near and Remote Sensing
We propose a novel convolutional neural network architecture for estimating geospatial functions such as population density, land cover, or land use. In our approach, we combine overhead andExpand
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DEEPFOCAL: A method for direct focal length estimation
Estimating the focal length of an image is an important preprocessing step for many applications. Despite this, existing methods for single-view focal length estimation are limited in that theyExpand
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On the location dependence of convolutional neural network features
As the availability of geotagged imagery has increased, so has the interest in geolocation-related computer vision applications, ranging from wide-area image geolocalization to the extraction ofExpand
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Understanding and Mapping Natural Beauty
While natural beauty is often considered a subjective property of images, in this paper, we take an objective approach and provide methods for quantifying and predicting the scenicness of an image.Expand
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A Pot of Gold: Rainbows as a Calibration Cue
Rainbows are a natural cue for calibrating outdoor imagery. While ephemeral, they provide unique calibration cues because they are centered exactly opposite the sun and have an outer radius of 42Expand
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