Paper
ClimateGAN: Raising Climate Change Awareness by Generating Images of\n Floods
Climate change is a major threat to humanity, and the actions required to\nprevent its catastrophic consequences include changes in both policy-making and\nindividual behaviour. However, taking action requires understanding the effects\nof climate change, even though they may seem abstract and distant. Projecting\nthe potential consequences of extreme climate events such as flooding in\nfamiliar places can help make the abstract impacts of climate change more\nconcrete and encourage action. As part of a larger initiative to build a\nwebsite that projects extreme climate events onto user-chosen photos, we\npresent our solution to simulate photo-realistic floods on authentic images. To\naddress this complex task in the absence of suitable training data, we propose\nClimateGAN, a model that leverages both simulated and real data for\nunsupervised domain adaptation and conditional image generation. In this paper,\nwe describe the details of our framework, thoroughly evaluate components of our\narchitecture and demonstrate that our model is capable of robustly generating\nphoto-realistic flooding.\n
Authors: Schmidt, Victor · Luccioni, Alexandra Sasha · Teng, Mélisande · Zhang, Tianyu · Reynaud, Alexia · Raghupathi, Sunand · Cosne, Gautier · Juraver, Adrien · Vardanyan, Vahe · Hernandez-Garcia, Alex · Bengio, Yoshua