  We introduce a deep learning approach to perform fine-grained population
estimation for displacement camps using high-resolution overhead imagery. We
train and evaluate our approach on drone imagery cross-referenced with
population data for refugee camps in Cox's Bazar, Bangladesh in 2018 and 2019.
Our proposed approach achieves 7.02% mean absolute percent error on sequestered
camp imagery. We believe our experiments with real-world displacement camp data
constitute an important step towards the development of tools that enable the
humanitarian community to effectively and rapidly respond to the global
displacement crisis.
