Small Target Detection

Infrared small target detection (IRSTD) focuses on accurately identifying tiny, low-contrast objects in infrared imagery, a crucial task with applications in defense, surveillance, and autonomous systems. Current research emphasizes developing lightweight yet accurate deep learning models, often incorporating attention mechanisms, transformer architectures, and multi-scale feature fusion techniques to overcome challenges posed by complex backgrounds and limited target information. These advancements are driving improvements in detection accuracy and efficiency, leading to more robust and deployable IRSTD systems across various applications.