Virtual avatar generation models as world navigators
<|reference_start|>Virtual avatar generation models as world navigators: We introduce SABR-CLIMB, a novel video model simulating human movement in rock climbing environments using a virtual avatar. Our diffusion transformer predicts the sample instead of noise in each diffusion step and ingests entire videos to output complete motion sequences. By leveraging a large proprietary dataset, NAV-22M, and substantial computational resources, we showcase a proof of concept for a system to train general-purpose virtual avatars for complex tasks in robotics, sports, and healthcare.<|reference_end|>
@article{mandava2024virtual,
    title={Virtual avatar generation models as world navigators},
    author={Sai Mandava},
    journal={arXiv preprint arXiv:2406.01056},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.01056},
    primaryClass={cs.CV cs.AI cs.HC cs.LG cs.RO}
}