Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

10-2019

Abstract

The current rapid advancements of computational hardware has opened the door for deep networks to be applied for real-time video processing, even on consumer devices. Appealing tasks include video super-resolution, compression artifact removal, and quality enhancement. These problems require high-quality datasets that can be applied for training and benchmarking. In this work, we therefore introduce two video datasets, aimed for a variety of tasks. First, we propose the Vid3oC dataset, containing 82 simultaneous recordings of 3 camera sensors. It is recorded with a multi-camera rig, including a high-quality DSLR camera, a high-end smartphone, and a stereo camera sensor. Second, we introduce the IntVID dataset, containing over 150 high-quality videos crawled from the internet. The datasets were employed for the AIM 2019 challenges for video super-resolution and quality mapping.

Keywords

Dataset; Video quality mapping; Video super resolution

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), Seoul, Korea, October 27-28

First Page

3609

Last Page

3616

ISBN

9781728150239

Identifier

10.1109/ICCVW.2019.00446

Publisher

Institute of Electrical and Electronics Engineers Inc.

City or Country

New York

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