Landmark Detection

Landmark detection, the process of identifying key points in images or 3D data, aims to accurately locate these features for various applications. Current research emphasizes improving accuracy and robustness, particularly in challenging scenarios like noisy images (e.g., ultrasound), incomplete data, and across diverse age groups or modalities, employing advanced architectures such as transformers, graph neural networks, and deep equilibrium models. These advancements have significant implications for diverse fields, including medical image analysis (e.g., automated diagnosis, surgical planning), robotics (e.g., navigation, object manipulation), and computer vision (e.g., facial expression recognition, human pose estimation). The development of more efficient and accurate landmark detection methods continues to drive progress in these areas.