XB
X. Baró
info
Please Note
<p>This page displays the records of the person named above and is not linked to a unique person identifier. This record may need to be merged to a profile.</p>
2 records found
1
Journal article
(2020)
-
Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah, Sergio Escalera, Yağmur Güç;lütürk, Umut Güçlü, Xavier Baro, Achmadnoer Sukma Wicaksana, Cynthia C.S. Liem, More Authors...
Explainability and interpretability are two critical aspects of decision support systems. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of apparent personality recognition. To the best of our knowledge, this is the first effort in this direction. We describe a challenge we organized on explainability in first impressions analysis from video. We analyze in detail the newly introduced data set, evaluation protocol, proposed solutions and summarize the results of the challenge. We investigate the issue of bias in detail. Finally, derived from our study, we outline research opportunities that we foresee will be relevant in this area in the near future.
...
Explainability and interpretability are two critical aspects of decision support systems. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of apparent personality recognition. To the best of our knowledge, this is the first effort in this direction. We describe a challenge we organized on explainability in first impressions analysis from video. We analyze in detail the newly introduced data set, evaluation protocol, proposed solutions and summarize the results of the challenge. We investigate the issue of bias in detail. Finally, derived from our study, we outline research opportunities that we foresee will be relevant in this area in the near future.
Conference paper
(2016)
-
Hugo Jair Escalante, Victor Ponce-López, Henning Müller, Martha Larson, Jun Wan, Michael A. Riegler, Baiyu Chen, Albert Clapés, Sergio Escalera, Isabelle Guyon, Xavier Baró, Pål Halvorsen
This paper provides an overview of the JointContest on Multimedia Challenges Beyond Visual Analysis.We organized an academic competition that focused on fourproblems that require e‚ective processing of multimodalinformation in order to be solved. Two tracks were devoted togesture spotting and recognition from RGB-D video, two fundamentalproblems for human computer interaction. Anothertrack was devoted to a second round of the €rst impressionschallenge of which the goal was to develop methods torecognize personality traits from short video clips. For thissecond round we adopted a novel collaborative-competitive(i.e., coopetition) setting. ‡e fourth track was dedicated tothe problem of video recommendation for improving userexperience. ‡e challenge was open for about 45 days, andreceived outstanding participation: almost 200 participantsregistered to the contest, and 20 teams sent predictions inthe €nal stage. ‡e main goals of the challenge were ful€lled:the state of the art was advanced considerably in the fourtracks, with novel solutions to the proposed problems (mostlyrelying on deep learning). However, further research is stillrequired. ‡e data of the four tracks will be available to allowresearchers to keep making progress in the four tracks
...
This paper provides an overview of the JointContest on Multimedia Challenges Beyond Visual Analysis.We organized an academic competition that focused on fourproblems that require e‚ective processing of multimodalinformation in order to be solved. Two tracks were devoted togesture spotting and recognition from RGB-D video, two fundamentalproblems for human computer interaction. Anothertrack was devoted to a second round of the €rst impressionschallenge of which the goal was to develop methods torecognize personality traits from short video clips. For thissecond round we adopted a novel collaborative-competitive(i.e., coopetition) setting. ‡e fourth track was dedicated tothe problem of video recommendation for improving userexperience. ‡e challenge was open for about 45 days, andreceived outstanding participation: almost 200 participantsregistered to the contest, and 20 teams sent predictions inthe €nal stage. ‡e main goals of the challenge were ful€lled:the state of the art was advanced considerably in the fourtracks, with novel solutions to the proposed problems (mostlyrelying on deep learning). However, further research is stillrequired. ‡e data of the four tracks will be available to allowresearchers to keep making progress in the four tracks