Visual Quality Assessment Databases, MMSP Konstanz
  • Home
  • VQA Databases
    • KonViD-150k Database
    • KonViD-1k Database
    • KonIQ-10k Database
    • KonIQ++ Database
    • KADID-10k Database
    • IQA-Experts-300
    • KonPatch-30k Database
    • KoSMo-1k Database
    • StudyMB 2.0 Database
    • Picturewise JND Data
    • KonJND-1k database
    • KonFiG-IQA Database
  • About
  • Contact

​KonViD-150k VQA Database

An extensive VQA database

Deep learning approaches have had limited success on existing VQA datasets, either artificial or authentically distorted. We introduce KonViD-150k, an in-the-wild VQA dataset that is substantially larger and diverse, allowing the exploration of training DNNs on massive video collections with coarse annotations. 

​The database consists of two parts:
​
  1. KonVid-150k-A: a coarsely annotated set of 152,265 videos, 5 seconds long, having five quality ratings each.
  2. KonVid-150k-B: 1,577 videos with a minimum of 89 ratings each. 

KonViD-150k provides a good testing ground for efficient VQA approaches, that are suitable to learn from large collections of videos, and can generalize well based on coarse annotations. Additionally, it is a great tool to investigate VQA methods with different annotation budget distribution strategies.

Cite us

KonViD-150k is freely available to the research community. If you use our database in your research, please cite both references:
@misc{konvid150k,
title = {The Konstanz 150k in-the-Wild Video Database (KonVid-150k)},
author = {G\"otz-Hahn, Franz and Hosu, Vlad and Lin, Hanhe and Saupe, Dietmar},
year = {2021},
url = {http://database.mmsp-kn.de}}

@inproceedings{hahn2021,
title = {KonVid-150k: A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild},
author = {G\"otz-Hahn, Franz and Hosu, Vlad and Lin, Hanhe and Saupe, Dietmar},
booktitle = {IEEE Access 9},
pages = {72139-72160},
year = {2021},
organization = {IEEE}}
​
Picture

Downloads

Browse KonVid-150k-B videos

KonVid-150k-A set

K150k-A ViDeos (.zip)
mirror
176 Gb
​download
K150k-A Scores (.csv)
5 Mb
download
K150k-A Votes (.csv)
96 Mb
​download

KonVid-150k-B set

K150k-B videos (.zip)
1.9 Gb
download
K150k-B Scores (.csv)
60 Kb
download
K150k-B Votes (.csv)
29 Mb
download

The aggregated scores files

  • video_name: Corresponds to a source file from KonVid-150k.
  • video_score: The mean opinion score of the corresponding video as used in the paper.
    • In the case of the K150k-A dataset, the MOS is comprised of 5 votes.
    • In the case of the K150k-B dataset, the MOS is comprised of at least 89 votes.
  • mos: The raw mean opinion score derived from the votes file, without any additional data cleaning

The raw votes files

  • video_name: Corresponds to a source file from KonVid-150k.
  • worker_id: The ID of the crowd worker.
  • video_score: quality score from 1 to 5 (individual responses from each crowd worker).
  • video_submission_time: The time the individual video was rated by a worker.
  • page_submission_time: The time the entire page was submitted by a worker.
  • page_starting_time: The time the page was initially loaded by a worker.
  • row_id: The ID of the row of 15 videos.
  • worker_country: Country of origin of the worker.
  • worker_channel: The channel the worker was coming from.
  • worker_trust: The trust rating of the worker.
Imprint | Privacy policy | About | Contact
Copyright "VQA Group at Universität Konstanz" © 2019-2021
  • Home
  • VQA Databases
    • KonViD-150k Database
    • KonViD-1k Database
    • KonIQ-10k Database
    • KonIQ++ Database
    • KADID-10k Database
    • IQA-Experts-300
    • KonPatch-30k Database
    • KoSMo-1k Database
    • StudyMB 2.0 Database
    • Picturewise JND Data
    • KonJND-1k database
    • KonFiG-IQA Database
  • About
  • Contact