Our new X account is live! Follow @wizwand_team for updates
WorkDL logo mark

Emotion Understanding in Videos Through Body, Context, and Visual-Semantic Embedding Loss

About

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.

Panagiotis Paraskevas Filntisis, Niki Efthymiou, Gerasimos Potamianos, Petros Maragos• 2020

Related benchmarks

TaskDatasetResultRank
Emotion RecognitionBoLD
mAP16.56
8
Emotion RecognitionBoLD official (test)
mR20.1141
3
Showing 2 of 2 rows

Other info

Follow for update