Omkar2118/datasets huggingface dataset:
SAT-MTB-VSR

SAT-MTB-VSR is a large-scale dataset for satellite video super-resolution made from original videos of Jilin-1, which is a subset of the satellite video multitasking dataset SAT-MTB. The dataset is cropped from 18 videos captured by the Jilin-1 video satellite, covering a wide range of terrains, such as cities, docks, airports, suburbs, forests, and deserts, with a resolution of about 1 m. And the videos contain dynamic scenes, such as moving cars, airplanes, trains, and ships, which test the ability of the VSR method to deal with moving targets of different sizes and speeds. At the same time, due to the motion of the satellite, the video contains changes in viewing angle and lighting.

It contains 431 videos, each of which is 100 consecutive frames, of which 413 are used as the training set and 18 as the validation set, and all the 18 validation sets are from different original videos, while the size of the images is 640 × 640. These images are downsampled 4× by bicubic interpolation to get 160 × 160 low-resolution images, thus obtaining the LR-HR training pairs.

Introducing paper: A Lightweight Recurrent Aggregation Network for Satellite Video Super-Resolution