3D Cuboid annotation involves placing a three-dimensional bounding box around objects in images or video frames. Unlike 2D bounding boxes, 3D cuboids provide depth, orientation, and spatial context—making it a critical tool for real-world object detection and tracking, especially in autonomous systems and robotics.
• Annotating cars, buses, pedestrians, and obstacles with 3D geometry
• LiDAR-camera fusion for real-world depth perception
• Enhancing path planning and obstacle avoidance systems
• Mapping construction equipment and building materials in 3D
• Site simulation for safety, logistics, and progress tracking
• Training machine vision systems for autonomous construction vehicles
• 3D object detection for pick-and-place robotics
• Drone-based 3D mapping of objects and terrain
• Training robots to interact accurately in dynamic environments
• Identifying boxes, pallets, and packages for robot handling
• Depth-aware automation for stacking, picking, and sorting
• Improved inventory management through spatial tracking
• 3D modeling of products for virtual stores
• Depth estimation for smart shelf management
• Virtual fitting rooms powered by 3D cuboid tracking
• Mapping terrain features and infrastructure in 3D
• Training models for elevation-aware segmentation
• Disaster response simulations using volumetric data
