Video Enhancement

Contains 800 sequences at various spatial resolutions from 270p to 2160p and has been evaluated on ten existing network architectures for four different coding tools. Source: BVI-DVC: A Training Database for Deep Video Compression

LDV is a dataset for video enhancement. It contains 240 videos with diverse categories of content, different kinds of motion and various frame-rates.

A dataset for compressed video quality enhancement.

I2-2000FPS is the first high-speed video dataset offering an unprecedented temporal resolution of 2000 frames per second (fps). Captured using the commercially available Chronos 1.4 high-speed CMOS camera, the dataset includes a diverse range of objects varying in size, shape, orientation, and motion, as well as various camera movements. This dataset is designed to enable research in areas such as motion analysis, object tracking, and scene understanding at extreme temporal resolutions. Potential applications span fields like sports analysis, robotics, autonomous navigation, and high-speed videography.

SEPE 8K dataset is made of 40 different 8K (8192 x 4320) video sequences and 40 variant 8K (8192 x 5464) images. The video sequences were captured at a framerate of 29.97 frames per second (FPS) and had been encoded into videos using AVC/H.264, HEVC/H.265, and AV1 codecs at resolutions from 8K to 480p. The images, video sequences, encoded videos, and various other statistics related to the media that make the dataset are stored online, published, and maintained on the repo on GitHub for non-commercial use. this proposed dataset is - as far as we know - the first to publish true 8K natural sequences; thus, it is important for the next level of applications dealing with multimedia such as video quality assessment, super-resolution, video coding, video compression, and many more. Paper: https://doi.org/10.1145/3587819.3592560

Vident-lab is a dataset of dental videos with multi-task labels to facilitate further research in relevant video processing applications. The dataset constitutes a low-quality frame, its high-quality counterpart, a teeth segmentation mask, and an inter-frame homography matrix. The homography warps the current frame to the previous frame with respect to the teeth. The dataset has the training, validation, and test sets of 300, 29, and 80 videos, respectively. Source: Multi-task Video Enhancement for Dental Interventions Image Source: https://arxiv.org/pdf/2210.16236v1.pdf