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MediaEval Multimedia Benchmarking

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  1. 2019-Emotion-and-Theme-Recognition-in-Music-Task 2019-Emotion-and-Theme-Recognition-in-Music-Task Public

    The goal of this task is to automatically recognize the emotions and themes conveyed in a music recording using machine learning algorithms.

    Python 37 3

  2. multimediaeval.github.io multimediaeval.github.io Public

    This repository holds the code to the https://multimediaeval.github.io/ website. The `master` branch contains only the `_site` folder built with Jekyll due to the use of a non-whitelisted plugin. T…

    HTML 5 31

  3. 2017-AcousticBrainz-Genre-Task 2017-AcousticBrainz-Genre-Task Public

    This task invites participants to predict genre and subgenre of unknown music recordings (songs) given automatically computed features of those recordings. The goal of our task is to understand how…

    TeX 4 1

  4. 2019-Pixel-Privacy-Task 2019-Pixel-Privacy-Task Public

    This task develops image enhancement approaches that project user privacy. Specifically, it is dedicated to creating technology that invisibly changes or visibly enhances images in such a way that …

    3 1

  5. 2017-Multimedia-Satellite-Task 2017-Multimedia-Satellite-Task Public

    This task requires participants to retrieve and link multimedia content from social media streams of events (e.g. flooding, fires, land clearing) that can be remotely sensed from satellite imagery.…

    2 3

  6. 2018-Pixel-Privacy-Task 2018-Pixel-Privacy-Task Public

    This task develops image enhancement approaches that project user privacy. Specifically, it is dedicated to creating technology that invisibly changes or visibly enhances images in such a way that …

    2 1

Repositories

Showing 9 of 9 repositories
  • multimediaeval.github.io Public

    This repository holds the code to the https://multimediaeval.github.io/ website. The `master` branch contains only the `_site` folder built with Jekyll due to the use of a non-whitelisted plugin. To edit content, please go to the `gh-page` branch.

    multimediaeval/multimediaeval.github.io’s past year of commit activity
  • 2019-Emotion-and-Theme-Recognition-in-Music-Task Public

    The goal of this task is to automatically recognize the emotions and themes conveyed in a music recording using machine learning algorithms.

    multimediaeval/2019-Emotion-and-Theme-Recognition-in-Music-Task’s past year of commit activity
    Python 37 3 0 2 Updated Jul 6, 2023
  • multimediaeval/2022-Medico-Multimedia’s past year of commit activity
    Python 0 1 0 1 Updated Jan 25, 2023
  • 2017-AcousticBrainz-Genre-Task Public

    This task invites participants to predict genre and subgenre of unknown music recordings (songs) given automatically computed features of those recordings. The goal of our task is to understand how genre classification can explore and address the subjective and culturally-dependent nature of genre categories.

    multimediaeval/2017-AcousticBrainz-Genre-Task’s past year of commit activity
    TeX 4 1 0 0 Updated Mar 20, 2022
  • multimediaeval/2021-Medico-Multimedia’s past year of commit activity
    Python 2 2 0 0 Updated Dec 21, 2021
  • multimediaeval/2020-Flood-Related-Multimedia-Task’s past year of commit activity
    Python 1 2 0 0 Updated Dec 17, 2020
  • 2019-Pixel-Privacy-Task Public

    This task develops image enhancement approaches that project user privacy. Specifically, it is dedicated to creating technology that invisibly changes or visibly enhances images in such a way that it is no longer possible to automatically infer the location at which they were taken.

    multimediaeval/2019-Pixel-Privacy-Task’s past year of commit activity
    3 1 0 0 Updated Sep 23, 2019
  • 2018-Pixel-Privacy-Task Public

    This task develops image enhancement approaches that project user privacy. Specifically, it is dedicated to creating technology that invisibly changes or visibly enhances images in such a way that it is no longer possible to automatically infer the location at which they were taken.

    multimediaeval/2018-Pixel-Privacy-Task’s past year of commit activity
    2 1 0 1 Updated Nov 29, 2018
  • 2017-Multimedia-Satellite-Task Public

    This task requires participants to retrieve and link multimedia content from social media streams of events (e.g. flooding, fires, land clearing) that can be remotely sensed from satellite imagery. The purpose of this task is to augment events captured by satellite images with social media reports in order to provide a more comprehensive view.

    multimediaeval/2017-Multimedia-Satellite-Task’s past year of commit activity
    2 3 1 0 Updated Sep 4, 2017

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