EpipolarPose is a self-supervised method for 3D human pose estimation that does not require 3D ground-truth data or camera extrinsics. During training, it estimates 2D poses from multi-view images and uses epipolar geometry to derive 3D pose and camera geometry, which then trains a 3D pose estimator. At test time, it takes a single RGB image as input to produce 3D pose output.