Omkar2118/datasets huggingface dataset:
QST
Full name: Quick Sky Time

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). Click [here](https://pan.baidu.com/s/1HUmSu-H1ot39ENeesVuz4Q ) (Key: qst1) to download the QST dataset.

Introducing paper: DTVNet: Dynamic Time-lapse Video Generation via Single Still Image
Stanford 3D Scanning Repository

In recent years, the number of range scanners and surface reconstruction algorithms has been growing rapidly. Many researchers, however, do not have access to scanning facilities or dense polygonal models. The purpose of this repository is to make some range data and detailed reconstructions available to the public.