42 citations · 101 across the 14 of their papers we have counts for
7 papers · 1 filter
Updating Street Maps using Changes Detected in Satellite Imagery
Favyen Bastani, Songtao He, Satvat Jagwani +5
Accurately maintaining digital street maps is labor-intensive. To address this challenge, much work has studied automatically processing geospatial data sources such as GPS traject…
Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding
Songtao He, Favyen Bastani, Satvat Jagwani +6
Inferring road graphs from satellite imagery is a challenging computer vision task. Prior solutions fall into two categories: (1) pixel-wise segmentation-based approaches, which pr…
RoadTagger: Robust Road Attribute Inference with Graph Neural Networks
Songtao He, Favyen Bastani, Satvat Jagwani +7
Inferring road attributes such as lane count and road type from satellite imagery is challenging. Often, due to the occlusion in satellite imagery and the spatial correlation of ro…
Inferring and Improving Street Maps with Data-Driven Automation
Favyen Bastani, Songtao He, Satvat Jagwani +7
Street maps are a crucial data source that help to inform a wide range of decisions, from navigating a city to disaster relief and urban planning. However, in many parts of the wor…
Machine-Assisted Map Editing
Favyen Bastani, Songtao He, Sofiane Abbar +4
Mapping road networks today is labor-intensive. As a result, road maps have poor coverage outside urban centers in many countries. Systems to automatically infer road network graph…
Group Anomaly Detection using Deep Generative Models
Raghavendra Chalapathy, Edward Toth, Sanjay Chawla
Unlike conventional anomaly detection research that focuses on point anomalies, our goal is to detect anomalous collections of individual data points. In particular, we perform gro…