Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition

Benchmark Model Rank Results
facial-expression-recognition-on-afewLResNet50E-IR (1 model with augmentation)–Accuracy(on validation set): 63.7%
facial-expression-recognition-on-afewLResNet50E-IR (1 model)–Accuracy(on validation set): 61.1%
facial-expression-recognition-on-afewLResNet50E-IR (5 models with augmentation)–Accuracy(on validation set): 65.5%
facial-expression-recognition-on-afewResNet50–Accuracy(on validation set): 65.5%
facial-expression-recognition-on-affectnetLResNet50E-IR–Accuracy (8 emotion): 53.925
facial-expression-recognition-on-fer-plusLResNet50E-IR–Accuracy: 89.257