bitmind/Quick-Sky-Time-Dataset

QST contains 1,167 video clips that are cut out from 216 time-lapse 4K videos collected from YouTube, which can be used for a variety of tasks, such as (high-resolution) video generation, (high-resolution) video prediction, (high-resolution) image generation, texture generation, image inpainting, image/video super-resolution, image/video colorization, image/video animating, etc. Each short clip contains multiple frames (from a minimum of 58 frames to a maximum of 1,200 frames, a total of 285,446 frames), and the resolution of each frame is more than 1,024 x 1,024. Specifically, QST consists of a training set (containing 1000 clips, totally 244,930 frames), a validation set (containing 100 clips, totally 23,200 frames), and a testing set (containing 67 clips, totally 17,316 frames).

Citation @inproceedings{dtvnet, title={DTVNet: Dynamic time-lapse video generation via single still image}, author={Zhang, Jiangning and Xu, Chao and Liu, Liang and Wang, Mengmeng and Wu, Xia and Liu, Yong and Jiang, Yunliang}, booktitle={European Conference on Computer Vision}, pages={300--315}, year={2020}, organization={Springer} }

@article{dtvnet+, title={DTVNet+: A High-Resolution Scenic Dataset for Dynamic Time-lapse Video Generation}, author={Zhang, Jiangning and Xu, Chao and Liu, Yong and Jiang, Yunliang}, journal={arXiv preprint arXiv:2008.04776}, year={2020} }