Can I read SeLiNet: Sentiment enriched Lightweight Network for Emotion Recognition in Images on EtoBox?

SeLiNet: Sentiment enriched Lightweight Network for Emotion Recognition in Images by Khargonkar, Tuneer; Choudhary, Shwetank; Kumar, Sumit; KR, Barath Raj is a scholarly article available to read on EtoBox.

What is SeLiNet: Sentiment enriched Lightweight Network for Emotion Recognition in Images about?

In this paper, we propose a sentiment-enriched lightweight network SeLiNet and an end-to-end on-device pipeline for contextual emotion recognition in images. SeLiNet model consists of body feature extractor, image aesthetics feature extractor, and learning-based fusion network which jointly estimates discrete emotion and human sentiments tasks. On the EMOTIC dataset, the proposed approach achieves an Average Precision (AP) score of 27.17 in comparison to the baseline AP score of 27.38 while reducing the model size by >85%. In addition, we report an on-device AP score of 26.42 with reduction in model size by >93% when compared to the baseline.

Author

Khargonkar, Tuneer; Choudhary, Shwetank; Kumar, Sumit; KR, Barath Raj

Published

2023

Language

EN