2024
Uncertainty-Guided Never-Ending Learning to Drive
CVPR 2024poster
We present a highly scalable self-training framework for incrementally adapting vision-based end-to-end autonomous driving policies in a semi-supervised manner i.e. over a continual stream of incoming video data. To facilitate large-scale model training (e.g. open web or unlabeled data) we do not as…