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LEAP: Making Privileged Geometry Supervision Effective for Visuomotor Learning
Privileged 3D supervision uses additional geometric information during training to guide RGB-based visuomotor policy learning, without requiring geometric inputs at deployment. However, low reconstruction error does not ensure that visual representations capture geometry useful for control. We ident
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