ACM International Conference on Multimedia Retrieval ICMR 2017

Challenge https://lnkd.in/dz3drn3A --- deploy machine learning/deep learning/artificial intelligence algorithms to automatically predict memorability scores for videos, which reflect the probability of a video being remembered by the viewer:

(i) video-based prediction: Participants are required to generate automatic systems that predict memorability scores of new videos based on a given video dataset that includes human performed memorability score annotations.

(ii) generalization prediction: Participants will train their systems on one of the two sources of annotated data we provide and will test them on the other source of data, to foster algorithms that are not data type dependent.

(iii) EEG-based prediction: Participants are required to use as input provided annotated neural signals, such as EEG—either alone, or in combination with other data sources—to predict the memorability.

here to participate https://lnkd.in/dKJhvJQQ. Upcoming deadline: Runs due on 15 November 2022. University of Essex, Universitatea POLITEHNICA din București, DCU, InterDigital, Inc., Massachusetts Institute of Technology (MIT).

https://multimediaeval.github.io/editions/2022/ Multimedia Evaluation Benchmark --- (1st call) --- MediaEval offers challenges in the form of shared tasks with the goal of developing and evaluating new and for multimedia , and .

Tasks are innovative, involving multiple modalities, e.g., , , , data, data and focusing on the human and social aspects of . Special emphasis is on promoting that makes multimedia a positive force for society.

Registration is now open and submissions will be due in November. This year’s tasks cover: : Multimedia Analysis of Disaster-Related Social Media Data; : A Game Analytics Challenge; : Fake News Detection; : Medical Multimedia Task: Transparent Tracking of Spermatozoa; : Multimodal Understanding of Smells in Texts and Images; : Relating news articles and images; : Fishing Trawler Video Analytics Task; : Predicting Video Memorability; : Fine Grained Action Detection and Classification of Table Tennis Strokes from videos; : Swimmers and Stroke Rate Detection in Elite Race Videos; : Urban Life and Air Pollution.

Results are presented at the MediaEval yearly workshop, which this year will be a hybrid workshop that will take place in Bergen, Norway 12-13 January 2023, co-located with the 29th International Conference on Multimedia Modeling, MMM2023, and also provide an opportunity for online participation.

special session on "Learning from scarce data challenges in the media domain" https://cbmi2022.org/call-for-special-session-papers/ -from-scarce-data @ 19th International Conference on Content-based Multimedia Indexing (CBMI 2022) AI4Media. Papers are due April 10, 2022.

Deep learning-based algorithms for multimedia content analysis need a large amount of annotated data for effective training, e.g., for image classification on the ImageNet dataset, each class comprises several thousand annotated samples. Having a dataset of insufficient size for training usually leads to a model which is prone to overfitting and performs poorly in practice. But in many real-world applications in multimedia content analysis, it is not possible or not viable to gather and annotate such a large training data. This may be due to the prohibitive cost of human annotation, ownership/copyright issues of the data, or simply not having enough media content of a certain kind available. To address this issue, a lot of research has been performed in recent years on learning from scarce data/learning from limited data. There are a variety of ways to work around the problem of data scarcity like using transfer learning, domain transfer or few-shot learning.

Unveiling Real-Life Effects of Online Photo Sharing https://lnkd.in/dJh-VTJP :

Images constitute a large part of the content shared on social networks. Their disclosure is often related to a particular context and users are often unaware of the fact that, depending on their privacy status, images can be accessible to third parties and be used for purposes which were initially unforeseen. For instance, it is common practice for employers to search information about their future employees online.

The objective of the task is to automatically score user photographic profiles via AI in a series of situations with strong impact on her/his life, e.g., search for a bank loan, an accommodation, a job as waitress/waiter, a job in IT. This is the second edition of the task. To train the algorithms, a data set of 1,000 user profiles with 100 photos per profile was created and annotated with an appeal score for a series of real-life situations via crowdsourcing.

https://lnkd.in/dc9WtyUa
Run submission: May 6, 2022
Working notes submission: May 27, 2022
CLEF 2022 conference: September 5-8, Bologna, Italy

CEA LIST AI4Media Universitatea POLITEHNICA din București ImageCLEF

@ https://www.imageclef.org/2022 : >> ImageCLEFcoral (4th edition) coral reef and , and image pixel-wise https://www.imageclef.org/2022/coral; >> ImageCLEFmedical (4th edition) automatic with , and analysis of https://www.imageclef.org/2022/medical; >> ImageCLEFaware (2nd edition) development of algorithms which raise the users’ about real-life impact of https://www.imageclef.org/2022/aware; >> ImageCLEFfusion (new) develop mechanisms and generate predictions with significantly higher performance than the individual systems https://www.imageclef.org/2022/fusion.
***Run submission is due May 6, 2022*** ImageCLEF AI4Media Universitatea POLITEHNICA din București HES-SO La Rochelle Université.

call-for-papers ACM on against @ ACM ICMR 2022, Newark, NJ, USA, June 27-30, 2022 https://mad2022.aimultimedialab.ro/ --- Disinformation campaigns are increasingly powered by advanced AI techniques and a lot of effort was put into the detection of fake content. While important, this is only a piece of the puzzle if one wants to address the phenomenon in a comprehensive manner. Whether a piece of information is considered fake or true often depends on the temporal and cultural contexts in which it is interpreted. This is for instance the case for scientific knowledge, which evolves at a fast pace, and whose usage in mainstream content should be updated accordingly --- our workshop to discuss multimedia AI methods to fight the ever growing online disinformation campaigns --- is due: February 17, 2022 Universitatea POLITEHNICA din București Εθνικό Κέντρο Έρευνας και Τεχνολογικής Ανάπτυξης CEA LIST Fraunhofer IDMT AI4Media ACM - Association for Computing Machinery.