Multi-model Ensemble Learning Method for Human Expression Recognition

Understand

Analysis of human affect plays a vital role in human-computer interaction (HCI) systems.

• Due to the difficulty in capturing large amounts of real-life data, most of the current methods have mainly focused on controlled environments, which limit their application scenarios.
• To tackle this problem, we propose our solution based on the ensemble learning method.
• Specifically, we formulate the problem as a classification task, and then train several expression classification models with different types of backbones--ResNet, EfficientNet and InceptionNet.