@inproceedings{li2021sat,
author = {Li, Zuoyue and Li, Zhenqiang and Cui, Zhaopeng and Qin, Rongjun and Pollefeys, Marc and Oswald, Martin Ralf},
title = {Sat2Vid: Street-view Panoramic Video Synthesis from a Single Satellite Image},
booktitle = {ICCV 2021},
year = {2021},
month = {October},
abstract = {We present a novel method for synthesizing both temporally and geometrically consistent street-view panoramic video from a single satellite image and camera trajectory. Existing cross-view synthesis approaches focus on images, while video synthesis in such a case has not yet received enough attention. For geometrical and temporal consistency, our approach explicitly creates a 3D point cloud representation of the scene and maintains dense 3D-2D correspondences across frames that reflect the geometric scene configuration inferred from the satellite view. As for synthesis in the 3D space, we implement a cascaded network architecture with two hourglass modules to generate point-wise coarse and fine features from semantics and per-class latent vectors, followed by projection to frames and an upsampling module to obtain the final realistic video. By leveraging computed correspondences, the produced street-view video frames adhere to the 3D geometric scene structure and maintain temporal consistency. Qualitative and quantitative experiments demonstrate superior results compared to other state-of-the-art synthesis approaches that either lack temporal consistency or realistic appearance. To the best of our knowledge, our work is the first one to synthesize cross-view images to video.},
url = {http://approjects.co.za/?big=en-us/research/publication/sat2vid-street-view-panoramic-video-synthesis-from-a-single-satellite-image/},
}