Name
Abstract | ||
|---|---|---|
This work presents an approach for emotion recognition in video through the interaction of visual, audio, and language information in an end-to-end learning manner with three key points: 1) lightweight feature extractor, 2) attention strategy, and 3) adaptive loss. We proposed a lightweight deep architecture with approximately 1 MB, which for the most crucial part, accounts for feature extraction,... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MMUL.2021.3080305 | IEEE MultiMedia |
Keywords | DocType | Volume |
Feature extraction,Convolution,Emotion recognition,Data mining,Face recognition,Visualization,Training | Journal | 28 |
Issue | ISSN | Citations |
2 | 1070-986X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Van T. Huynh | 1 | 5 | 2.85 |
| Hyungjeong Yang | 2 | 455 | 47.05 |
| Guee-Sang Lee | 3 | 0 | 0.34 |
| Soo-Hyung Kim | 4 | 191 | 49.03 |