Robot foundation models have shown remarkable performance in robot control, yet adapting them to a new task still relies heavily on teleoperated demonstrations. Egocentric human videos offer a scalabl
RoboTryOn translates human demonstration videos into robot videos to train control policies without real robot demonstrations, improving success rates and reducing data collection costs.
Robot foundation models have shown remarkable performance in robot control, yet adapting them to a new task still relies heavily on teleoperated demonstrations. Egocentric human videos offer a scalable substitute, but overlaying rendered robots on human videos or retargeting human poses into robot actions leaves significant visual or action gaps for high-DoF robot embodiments. To address this limitation, we propose RoboTryOn, which treats human-to-robot translation as virtual try-on: try-on keeps the person and swaps the garment, RoboTryOn keeps the demonstrated motion and swaps the human for the robot. Specifically, RoboTryOn converts a human video into a video of the target robot…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
RoboTryOn: Synthesizing Dexterous Robot Demonstrations from Human Videos via Virtual Try-On was first seen on Hugging Face · Daily papers on Nov 4, 2026. Since then it has appeared in 7 checks on 2 different days. Its best position was #25 of 30, reached on Nov 5, 03:28 UTC. It dropped off the list after Nov 5, 11:28 UTC.
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Not at the moment. It was last on the list on Nov 5, 11:28 UTC, after 2 days of trending.
#25 on Hugging Face · Daily papers, on Nov 5, 03:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 4, 2026 and has been on the list on 2 days (7 checks) since.