| dc.creator | Filntisis P.P., Efthymiou N., Potamianos G., Maragos P. | en |
| dc.date.accessioned | 2023-01-31T07:38:02Z | |
| dc.date.available | 2023-01-31T07:38:02Z | |
| dc.date.issued | 2020 | |
| dc.identifier | 10.1007/978-3-030-66415-2_52 | |
| dc.identifier.isbn | 9783030664145 | |
| dc.identifier.issn | 03029743 | |
| dc.identifier.uri | http://hdl.handle.net/11615/71592 | |
| dc.description.abstract | We present our winning submission to the First International Workshop on Bodily Expressed Emotion Understanding (BEEU) challenge. Based on recent literature on the effect of context/environment on emotion, as well as visual representations with semantic meaning using word embeddings, we extend the framework of Temporal Segment Network to accommodate these. Our method is verified on the validation set of the Body Language Dataset (BoLD) and achieves 0.26235 Emotion Recognition Score on the test set, surpassing the previous best result of 0.2530. © 2020, Springer Nature Switzerland AG. | en |
| dc.language.iso | en | en |
| dc.source | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101415771&doi=10.1007%2f978-3-030-66415-2_52&partnerID=40&md5=5417226f91b11036b6ddec26f0ecb894 | |
| dc.subject | Embeddings | en |
| dc.subject | Semantics | en |
| dc.subject | Statistical tests | en |
| dc.subject | Body language | en |
| dc.subject | Emotion recognition | en |
| dc.subject | Emotion understanding | en |
| dc.subject | International workshops | en |
| dc.subject | Temporal segments | en |
| dc.subject | Test sets | en |
| dc.subject | Visual representations | en |
| dc.subject | Visual semantics | en |
| dc.subject | Computer vision | en |
| dc.subject | Springer Science and Business Media Deutschland GmbH | en |
| dc.title | Emotion Understanding in Videos Through Body, Context, and Visual-Semantic Embedding Loss | en |
| dc.type | conferenceItem | en |
