Article

VEGA: Training Navigation VLAs with In-the-Wild Egocentric Video and Geometric Trajectory Supervision

VEGA proposes a method for training navigation Vision-Language-Action (VLA) models from unlabeled egocentric navigation videos. It reconstructs local scene geometry from monocular video, samples text, image, and spatial waypoint goals, and generates obstacle-avoidance trajectories, then uses these trajectories to train a flow-matching VLA navigation policy; geometry is used only during training.

Part of the event: VEGA: Training Navigation VLAs from First-Person Videos

This page provides a summary and source link only.