Create README.md

README.md

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+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}
+}