CALL FOR PARTICIPATION The One-Minute Gradual-Emotion Recognition (OMG-Emotion) held in partnership with the WCCI/IJCNN 2018 in Rio de Janeiro, Brazil. https://www2.informatik.uni-hamburg.de/wtm/OMG-EmotionChallenge/  I. Aim and Scope Our One-Minute-Gradual Emotion Dataset (OMG-Emotion Dataset) is composed of 420 relatively long emotion videos with an average length of 1 minute, collected from a variety of Youtube channels. The videos were selected automatically based on specific search terms related to the term ``monologue''. Using monologue videos allowed for different emotional behaviors to be presented in one context and that changes gradually over time. Videos were separated into clips based on utterances, and each utterance was annotated by at least five independent subjects using the Amazon Mechanical Turk tool. To maintain the contextual information for each video, each annotator watched the clips of a video in sequence and had to annotate each video using an arousal/valence scale and a categorical emotion based on the universal emotions from Ekman. We release the dataset with the gold standar for arousal and valence as well the invidivual annotations for each reviewer, which can help the development of different models. We will calculate the final Congruence Correlation Coefficient  against the gold standard for each video. We also distribute the transcripts of what was spoken in each of the videos, as the contextual information is important to determine gradual emotional change through the utterances. The participants are encouraged to use crossmodal information in their models, as the videos were labeled by humans without distinction of any modality. We also will let available to the participant teams a set of scripts which will help them to pre-process the dataset and evaluate their model during in the training phase. We encourage the use of neural-computation models based on deep learning, sel-organization and recurrent neural networks, just to mention some of them, as they present the sate-of-the-art performance in such tasks. II. How to Participate To participate, please send us an email to barros@informatik.uni-hamburg.de with the title "OMG-Emotion Recognition Team Registration". This e-mail must contain the following information: Team Name Team Members Affiliation Each team can have a maximum of 5 participants. You will receive from us the access to the dataset and all the important information about how to train and evaluate your models. For the final submission, each team will have to send us a .csv file containing the final arousal/valence values for each of the utterances on the test dataset. We also request a link to a GitHub repository where your solution must be stored, and a link to an ArXiv paper with 4-6 pages describing your model and results. The best papers will be invited to submit their detailed research to a journal yet to be specified. Also, the best participating teams will hold an oral presentation about their solution during the WCCI/IJCNN 2018 conference. III. Important Dates Publishing of training and validation data with annotations: March 14, 2018. Publishing of the test data, and an opening of the online submission: April 11, 2018. Closing of the submission portal: April 13, 2018. Announcement of the winner through the submission portal: April 18, 2018. IV. Organization Pablo Barros, University of Hamburg, Germany Egor Lakomkin, University of Hamburg, Germany Henrique Siqueira, Hamburg University, Germany Alexander Sutherland, Hamburg University, Germany Stefan Wermter, Hamburg University, Germany -- Dr.rer.nat. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/