Bounding box annotation is a process of manually labeling or annotating an image with a bounding box around a specific object or feature of interest. This type of annotation techniques is commonly used in computer vision and machine learning applications, particularly in the field of object detection. 

Segmentation annotation is the process of labeling or annotating objects within sensor data, such as images or point clouds, by outlining their boundaries using polygons. Each object is categorized and marked with a polygon to define its exact location and extent within the data. This helps train computer vision based AI models.

3D cuboid annotation involves labeling objects in 3D space using cuboid shapes. This provides accurate spatial information for various tasks like object detection, tracking, and more in robotics and autonomous driving. Cuboid Annotation is used for building a 3D simulated world from 2D information.