Virtual avatar generation models as world navigators
Fuente:
arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910469344722944 |
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| author | Mandava, Sai |
| author_facet | Mandava, Sai |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_01056 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Virtual avatar generation models as world navigators Mandava, Sai Computer Vision and Pattern Recognition Artificial Intelligence Human-Computer Interaction Machine Learning Robotics 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. |
| title | Virtual avatar generation models as world navigators |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Human-Computer Interaction Machine Learning Robotics |
| url | https://arxiv.org/abs/2406.01056 |