83 citations · 291 across the 33 of their papers we have counts for
4 papers · 1 filter
A Weakly Supervised Approach for Estimating Spatial Density Functions from High-Resolution Satellite Imagery
Nathan Jacobs, Adam Kraft, Muhammad Usman Rafique +1
We propose a neural network component, the regional aggregation layer, that makes it possible to train a pixel-level density estimator using only coarse-grained density aggregates,…
What Goes Where: Predicting Object Distributions from Above
Connor Greenwell, Scott Workman, Nathan Jacobs
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 image…
Learning to Look around Objects for Top-View Representations of Outdoor Scenes
Samuel Schulter, Menghua Zhai, Nathan Jacobs +1
Given a single RGB image of a complex outdoor road scene in the perspective view, we address the novel problem of estimating an occlusion-reasoned semantic scene layout in the top-…
Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees
Hamid Hamraz, Nathan B. Jacobs, Marco A. Contreras +1
The purpose of this study was to investigate the use of deep learning for coniferous/deciduous classification of individual trees from airborne LiDAR data. To enable efficient proc…