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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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Large-scale geo-facial image analysis
While face analysis from images is a well-studied area, little work has explored the dependence of facial appearance on the geographic location from which the image was captured. To fill this gap, weExpand
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Learning to Map Nearly Anything
Looking at the world from above, it is possible to estimate many properties of a given location, including the type of land cover and the expected land use. Historically, such tasks have relied onExpand
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A fast method for estimating transient scene attributes
We propose the use of deep convolutional neural networks to estimate the transient attributes of a scene from a single image. Transient scene attributes describe both the objective conditions, suchExpand
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GeoFaceExplorer: exploring the geo-dependence of facial attributes
The images uploaded to social networking websites are a rich source of information about the appearance of people around the world. We present a system, GeoFaceExplorer, for collecting, processing,Expand
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What Goes Where: Predicting Object Distributions from Above
In this work, we propose a cross-view learning approach, in which images captured from a ground-level view are used as weakly supervised annotations for interpreting overhead imagery. The outcome isExpand
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Learning Geo-Temporal Image Features
We propose to implicitly learn to extract geo-temporal image features, which are mid-level features related to when and where an image was captured, by explicitly optimizing for a set of location andExpand
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Weakly-Supervised Feature Learning via Text and Image Matching
When training deep neural networks for medical image classification, obtaining a sufficient number of manually annotated images is often a significant challenge. We propose to use textual findings,Expand
Implicit Land Use Mapping Using Social Media Imagery
Land use classification is a central remote sensing task with a broad range of applications. Typically this is represented as a supervised learning problem, the first step of which is to develop aExpand
Single Image Cloud Detection via Multi-Image Fusion
Artifacts in imagery captured by remote sensing, such as clouds, snow, and shadows, present challenges for various tasks, including semantic segmentation and object detection. A primary challenge inExpand