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Presenting DemoDiffusion: An extremely simple approach enabling a pre-trained 'generalist' diffusion policy to follow a human-demonstration for a novel task during inference One-shot human imitation without requiring any paired human-robot data or online RL 🙂 1/n

Homanga Bharadhwaj

3,018 subscribers

32,830 просмотров • 11 месяцев назад •via X (Twitter)

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Комментарии: 8

Фото профиля Homanga Bharadhwaj

Homanga Bharadhwaj11 месяцев назад

The key insight of DemoDiffusion is to start the denoising process for the diffusion policy with the re-targeted human hand trajectory (instead of starting from pure noise) This simple approach doesn't require fine-tuning/updating the diffusion policy in any way! 2/n

Фото профиля Homanga Bharadhwaj

Homanga Bharadhwaj11 месяцев назад

Results show that DemoDiffusion can perform tasks that the pre-trained diffusion policy (pi-0) fails at zero-shot, just from one human demonstration of the task! 3/n

Фото профиля Homanga Bharadhwaj

Homanga Bharadhwaj11 месяцев назад

We even see zero-shot generalization to objects different from what the human demonstration was shown on! This suggests DemoDiffusion is able to exploit the semantic/spatial generalization of the pre-trained diffusion policy - while guiding it based on the human demo 4/n

Фото профиля Homanga Bharadhwaj

Homanga Bharadhwaj11 месяцев назад

DemoDiffusion is made possible by @sungj1026 's amazing lead, and @shubhtuls 's precise insights on diffusion models @CMU_Robotics Code, Videos, Paper: (finally, thanks to @physical_int for pi0 and @geopavlakos @JitendraMalikCV et al. for HaMeR) n/n

Фото профиля Homanga Bharadhwaj

Homanga Bharadhwaj11 месяцев назад

@shubhtuls @CMU_Robotics @physical_int @geopavlakos @JitendraMalikCV Also check out this alternate thread from @sungj1026 on DemoDiffusion (n+1)/n

Фото профиля Ted Xiao

Ted Xiao11 месяцев назад

Nice work! Warm-starting the denoising progress with a human prior is very smart.

Фото профиля Himanshu Kumar

Himanshu Kumar11 месяцев назад

Perhaps true mastery lies in effortless adaptation, not rigid programming.

Фото профиля Arsen Ibragimov

Arsen Ibragimov11 месяцев назад

Thats clever, skipping the fine-tuning part is a flex

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