Multimedia Grand Challenge
The Multimedia Grand Challenge presents a set of problems and issues from industry leaders and top academic institutions, geared to engage the Multimedia research community in solving relevant, interesting and challenging questions for multimedia on a 3-5 year vision.
The Multimedia Grand Challenge was first presented as part of ACM Multimedia 2009 and has established itself as a prestigious competition in the multimedia community. This year’s conference will continue the tradition by repeating previous challenges and by introducing brand new challenges.
- Content-based Video Relevance Prediction Challenge
- Description: Video streaming platforms depend heavily on the video recommender system to help viewers discover videos they would enjoy. Most existing recommendation systems compute the video relevance based on viewers’ implicit feedbacks. However, this kind of method performs poorly for the “cold-start” content – videos newly added to the library that need to bootstrap the relevance score with very little viewer feedbacks. One promising approach to solve the “cold-start” problem is analyzing the video content itself to predict relevance. In this challenge, Hulu will provide some real-world video content – movies/TV-series videos, along with ground-truth video-to-video relevance table derived from viewers’ implicit feedbacks. The goal of the challenge is to explore effective approaches for content-based video recommendation.
- Website: https://github.com/mengyi-liu/cbvrp-acmmm-2018
- Perfect Corp. Challenge 2018: Half Million Beauty Product Image Recognition
- Description: Given a real-world image containing one beauty or personal care item, the Perfect Corp. Challenge 2018 is to match the real-world example of this item to the same item in our Perfect-500K data set. This is a practical but extremely challenging task, given the limitation that only images from e-commerce sites are available in Perfect-500K and no real-world examples will be provided in advance.
- Website: https://challenge2018.perfectcorp.com/index.html
- Mirror Website: https://mm18grandchallenge.github.io/Perfect/index.html
- Social Media Headline Prediction (SMHP)
Description: On social media, authors often want to see their information shared more widely, potentially reaching thousands of readers in a short amount of time. Headline prediction is thus one of the most desired and powerful tools to crack the secret of popular social media content. Therefore, our challenge task is designed to get a deeper understanding of the temporal evolution of social media headlines. Given sequential and continuous post sharing data before a specific date from social media, the problem is to predict how popular of new posts will be for the near future and which would be the headlines
The submissions (max 5 pages with the 5th page exclusively reserved for references) should be formatted according to ACM Multimedia formatting guidelines. Multimedia Grand Challenge reviewing is double-blind so authors shouldn’t reveal their identity in the paper. The finalists will be selected by a committee consisting of academia and industry representatives, based on novelty, presentation, scientific interest of the approaches, and for the evaluation-based challenges, on the performance against the task.
Accepted submissions will be published in the conference proceedings, and will be presented in a special event during the ACM Multimedia 2018 conference in Seoul, Korea. At the conference, finalists will be requested to introduce their solutions, give a quick demo, and take questions from the judges and the audience.
Winners will be selected for Multimedia Grand Challenge awards based on their presentation.
- Significantly address one of the challenges posted on the website.
- Depict working, presentable systems or demos, using the grand challenge dataset where provided.
- Describe why the system presents a novel and interesting solution.
Submission deadline 8 July 2018
Notification of acceptance 5 Aug 2018
Camera-ready 12 Aug 2018
For any questions regarding the Grand Challenges you can email the Multimedia Grand Challenge Chairs:
- Hayley Hung, Delft University of Technology (email@example.com)
- Shuqiang Jiang, Chinese Academy of Sciences (firstname.lastname@example.org)