Name
Title | ||
|---|---|---|
Group-Level Emotion Recognition Using Hybrid Deep Models Based on Faces, Scenes, Skeletons and Visual Attentions. |
Abstract | ||
|---|---|---|
This paper presents a hybrid deep learning network submitted to the 6th Emotion Recognition in the Wild (EmotiW 2018) Grand Challenge [9], in the category of group-level emotion recognition. Advanced deep learning models trained individually on faces, scenes, skeletons and salient regions using visual attention mechanisms are fused to classify the emotion of a group of people in an image as positive, neutral or negative. Experimental results show that the proposed hybrid network achieves 78.98% and 68.08% classification accuracy on the validation and testing sets, respectively. These results outperform the baseline of 64% and 61%, and achieved the first place in the challenge.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3242969.3264990 | ICMI |
Keywords | Field | DocType |
EmotiW 2018, Group-level Emotion Recognition, Multi-model, Scene Understanding, Visual Attention | Social group,Computer vision,Computer science,Emotion recognition,Speech recognition,Visual attention,Artificial intelligence,Deep learning,Salient | Conference |
ISBN | Citations | PageRank |
978-1-4503-5692-3 | 3 | 0.39 |
References | Authors | |
22 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Guo | 1 | 31 | 15.25 |
| Bin B. Zhu | 2 | 22 | 10.46 |
| Luisa F. Polania | 3 | 131 | 9.54 |
| charles g boncelet | 4 | 27 | 10.06 |
| Kenneth E. Barner | 5 | 812 | 70.19 |