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

Been exploring how to train computer vision models without the painful step of manual labeling—by letting the system generate its own perfectly labeled images. Real datasets are limited in terms of subjects, environments, shapes, poses, etc.

The idea: start with a 3D mesh of a human body, render it photorealistically, and automatically extract all the labels (like body points, segmentation masks, depth, etc.) directly from the 3D data. No hand-labeling, no guesswork—just consistent and accurate ground truths every time.

Here’s a short video showing how it works. Generate image → align shape → align pose → align depth → extract ground truth labels → filter negatives against known mask.