116 citations · 145 across the 5 of their papers we have counts for
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cs.CV2024★ 1 cited
Robust Disaster Assessment from Aerial Imagery Using Text-to-Image Synthetic Data
Tarun Kalluri, Jihyeon Lee, Kihyuk Sohn +4
We present a simple and efficient method to leverage emerging text-to-image generative models in creating large-scale synthetic supervision for the task of damage assessment from a…
cs.CV2020★ 27 cited
Assessing Post-Disaster Damage from Satellite Imagery using Semi-Supervised Learning Techniques
Jihyeon Lee, Joseph Z. Xu, Kihyuk Sohn +8
To respond to disasters such as earthquakes, wildfires, and armed conflicts, humanitarian organizations require accurate and timely data in the form of damage assessments, which in…
cs.CV2019★ 116 cited
Building Damage Detection in Satellite Imagery Using Convolutional Neural Networks
Joseph Z. Xu, Wenhan Lu, Zebo Li +2
In all types of disasters, from earthquakes to armed conflicts, aid workers need accurate and timely data such as damage to buildings and population displacement to mount an effect…