Semantic Interaction

Semantic interaction research focuses on improving how humans and machines understand and interact using meaning-based representations, rather than just raw data. Current efforts concentrate on enhancing model performance through techniques like incorporating label relationships into graph structures, leveraging deep learning for feature extraction and fine-tuning based on user interactions, and developing data augmentation methods that preserve semantic coherence. This work is significant for advancing human-computer interaction, particularly in areas like object detection, multi-object tracking, and visual analytics, by enabling more intuitive and efficient interactions with complex systems.