Object Annotation

Object annotation, the process of labeling objects within images or videos, is crucial for training computer vision models, but manual annotation is expensive and time-consuming. Current research focuses on developing automated or semi-automated annotation methods, often leveraging vision-centric approaches that reduce reliance on other data sources like LiDAR, and employing techniques like iterative annotation refinement and probabilistic models to improve efficiency and accuracy. These advancements are significantly impacting various fields, enabling the development of more robust and accurate models for applications ranging from autonomous driving to medical image analysis by reducing the need for extensive manual labeling.