DeepLandscape: Adversarial Modeling of Landscape Videos [teaser]
Channel: Oleg Khomenko
Date: 25/08/2020

We build a new model of landscape videos that can be trained on a mixture of static landscape images as well as landscape animations. Our architecture extends StyleGAN model by augmenting it with parts that allow to model dynamic changes in a scene.
Once trained, the model can be used to generate realistic time-lapse landscape videos with moving objects and time-of-the-day changes. Furthermore, by fitting the learned models to a static landscape image, the latter can be reenacted in a realistic way.

The model outperforms the previous state-of-the-art methods according to widely used metrics and human evaluation.

Conference: ECCV2020
Project page: https://saic-mdal.github.io/deep-landscape/
Authors:
E. Logacheva, R. Suvorov, O. Khomenko, A. Mashikhin, and V. Lempitsky.
"DeepLandscape: Adversarial Modeling of Landscape Videos".