I am very happy to announce that we have a winner 🙂
Before I congratulate the teams, I would like to say I am very happy with the engagement of all the teams during the challenge. Preparing this challenge, from the design and data collection to the dissemination and organization was a … challenge 😀
But we are very pleased with the outcome, and we also hope that the dataset and the evaluation protocol can contribute to the area of artificial empathy. I hope that we can collaborate and discuss with all of you in the future and that our paths cross again soon.
We were very impressed by all your efforts. You got our message that pure instantaneous perception would not work, and most of the solutions made use of some sort of temporal context. Also, amazing to see the use of different modalities and the solutions for multisensory synchronization.
By analyzing the results, we can see that Story 7 was the most challenging one. Probably due to the actor in story 7 were quite different from the others. Maybe this could a point to focus on future work: how to deal with this problem.
Was a very close competition for both tracks. Here are the final results: https://www2.informatik.uni-
hamburg.de/wtm/omgchallenges/ omg_empathy2018_results2018. html
Not all the teams sent us a short description of their submission. If you still want a short description of the table, please send it to me. Links to the papers will be added as soon as we have the reviewing process done. If any information is wrong or missing, please let me know!
I want to congratulate the Alpha-City team to win the 2018 OMG–Empathy Challenge on both tracks! Their solution included different modalities and contextual processing to achieve 0.17CCC for both tracks. Congratulations!
For the personalized track, the USTC-AC and the A*STAR AI team achieved both 0.14 CCC. Both teams used different solutions, all based on the synchronization of multisensory information. So both teams are awarded the 2nd place. The USTC-AC also obtained the 3rd best submission, with a CCC of 0.13, however as they were awarded the second place already, the Rosie team got the third place, with a CCC of 0.8. They proposed a solution based on processing audio, images, and semantic information. Congratulations!!
For the generalized track, the same happened: the USTC-AC and the A*STAR AI team were awarded a joint second place. The EIHW team was awarded third place. They provide a solution based on audio and images processing.
We will prepare and send to the three best teams of each track a certificate stating their achievements in the next weeks.
And I think that’s it. Once again, thank you so much for all the teams and their efforts on participating in the challenge. Was super fun to organize it and to interact with you all.
I published a Twitter with the link to the results, so if you want to like it/share it, be my guest: https://twitter.com/PBarros_
Pablo, Angelica, and Nikhil