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ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation
[article]
2022
arXiv
pre-print
Manipulating volumetric deformable objects in the real world, like plush toys and pizza dough, bring substantial challenges due to infinite shape variations, non-rigid motions, and partial observability. We introduce ACID, an action-conditional visual dynamics model for volumetric deformable objects based on structured implicit neural representations. ACID integrates two new techniques: implicit representations for action-conditional dynamics and geodesics-based contrastive learning. To
arXiv:2203.06856v3
fatcat:7t4yshts4ngudk6ywcw555phn4