No humans needed: AI generates and labels its own training data

Manual labeling is a well-known bottleneck in training computer vision models—it’s slow, expensive, and raises privacy concerns when using real human data. I’ve been experimenting with an alternative: generating synthetic data from 3D human body meshes.

By rendering these meshes with realistic lighting, clothing, and backgrounds, it’s possible to generate accurate labels automatically—keypoints, segmentation, depth maps, and more. This approach makes it easier to scale datasets, control variability, and avoid the limitations of real-world image collection.