2 citations · 5 across the 8 of their papers we have counts for
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cs.RO2023★ 2 cited
Cold Diffusion on the Replay Buffer: Learning to Plan from Known Good States
Zidan Wang, Takeru Oba, Takuma Yoneda +3
Learning from demonstrations (LfD) has successfully trained robots to exhibit remarkable generalization capabilities. However, many powerful imitation techniques do not prioritize…
cs.CV2023
R2-Diff: Denoising by diffusion as a refinement of retrieved motion for image-based motion prediction
Takeru Oba, Norimichi Ukita
Image-based motion prediction is one of the essential techniques for robot manipulation. Among the various prediction models, we focus on diffusion models because they have achieve…
cs.CV2023★ 2 cited
Data-Driven Stochastic Motion Evaluation and Optimization with Image by Spatially-Aligned Temporal Encoding
Takeru Oba, Norimichi Ukita
This paper proposes a probabilistic motion prediction method for long motions. The motion is predicted so that it accomplishes a task from the initial state observed in the given i…