Building Robust 3D Data Pipelines: From Manual Cuboids to Scalable Workflows

As point cloud datasets grow larger and more complex, drawing cuboids frame by frame becomes the slowest, and most expensive, part of building production-ready models. In this 20-minute masterclass, we’ll show how teams are replacing manual-first 3D annotation with autolabeling workflows, where models generate high-quality cuboids and humans focus on review, refinement, and edge cases. In this fast-paced session you’ll learn how to: - Use 3D cuboid autolabeling to generate high-quality LiDAR annotations automatically - Review, refine, and approve model-generated cuboids instead of drawing them from scratch - Combine temporal context and point cloud data to improve cuboid consistency - Decide where human-in-the-loop review adds the most value