  What did it feel like to walk through a city from the past? In this work, we
describe Nostalgin (Nostalgia Engine), a method that can faithfully reconstruct
cities from historical images. Unlike existing work in city reconstruction, we
focus on the task of reconstructing 3D cities from historical images. Working
with historical image data is substantially more difficult, as there are
significantly fewer buildings available and the details of the camera
parameters which captured the images are unknown. Nostalgin can generate a city
model even if there is only a single image per facade, regardless of viewpoint
or occlusions. To achieve this, our novel architecture combines image
segmentation, rectification, and inpainting. We motivate our design decisions
with experimental analysis of individual components of our pipeline, and show
that we can improve on baselines in both speed and visual realism. We
demonstrate the efficacy of our pipeline by recreating two 1940s Manhattan city
blocks. We aim to deploy Nostalgin as an open source platform where users can
generate immersive historical experiences from their own photos.
