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Handling Image and Label Resolution Mismatch in Remote Sensing
Scott Workman, Armin Hadzic, M. Usman Rafique
Though semantic segmentation has been heavily explored in vision literature, unique challenges remain in the remote sensing domain. One such challenge is how to handle resolution m…
Revisiting Near/Remote Sensing with Geospatial Attention
Scott Workman, M. Usman Rafique, Hunter Blanton +1
This work addresses the task of overhead image segmentation when auxiliary ground-level images are available. Recent work has shown that performing joint inference over these two m…
Augmenting Depth Estimation with Geospatial Context
Scott Workman, Hunter Blanton
Modern cameras are equipped with a wide array of sensors that enable recording the geospatial context of an image. Taking advantage of this, we explore depth estimation under the a…
Learning a Dynamic Map of Visual Appearance
Tawfiq Salem, Scott Workman, Nathan Jacobs
The appearance of the world varies dramatically not only from place to place but also from hour to hour and month to month. Every day billions of images capture this complex relati…
A Structure-Aware Method for Direct Pose Estimation
Hunter Blanton, Scott Workman, Nathan Jacobs
Estimating camera pose from a single image is a fundamental problem in computer vision. Existing methods for solving this task fall into two distinct categories, which we refer to…
Dynamic Traffic Modeling From Overhead Imagery
Scott Workman, Nathan Jacobs
Our goal is to use overhead imagery to understand patterns in traffic flow, for instance answering questions such as how fast could you traverse Times Square at 3am on a Sunday. A…