Facial Expression Recognition

Facial expression recognition (FER) aims to automatically identify human emotions from facial images or videos, seeking to improve human-computer interaction and other applications. Current research emphasizes improving accuracy and robustness in challenging conditions (e.g., partial occlusion, low light, diverse demographics), often employing deep convolutional neural networks, transformers, and graph convolutional networks, along with techniques like data augmentation and transfer learning. Significant advancements are being made in model interpretability and generalization across domains, with implications for fields ranging from healthcare and robotics to virtual reality and affective computing.