Object Counting

Object counting in images and videos aims to automatically determine the number of objects present, a task crucial for various applications like traffic monitoring, wildlife conservation, and robotics. Current research emphasizes developing class-agnostic methods that can count diverse objects without extensive training data for each category, often employing transformer-based architectures, density map regression, and techniques like contrastive learning and few-shot learning. These advancements are improving the accuracy and efficiency of object counting, reducing reliance on laborious manual annotation, and enabling broader applicability across diverse domains.