Author

M. Strong

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Preprint Oct 2026

Real2Sem2Real: 3D Semantic Augmentations for Robot Learning from a Single Human RGB Demonstration

Human video scales easily and does not need robot hardware, but existing methods require depth sensing, overlay the robot onto 2D video, or generate data only for the demonstrated objects. We present Real2Sem2Real (R2Sem2R), a real-to-semantic-to-real pipeline that turns one monocular RGB video of a human demonstration...

M. Strong, Ankush Dhawan, J. Poffet et al. · 0 citations

Preprint Sep 2026

VisTacAlign: Co-Training Dexterous Policies on Tactile Human and Robot Demonstrations using Visual-Tactile Alignment

Human demonstrations are a cheap source of data for dexterous manipulation, but co-training a robot policy on them requires closing the human--robot gap in every modality the policy consumes. We present VisTacAlign, a framework for co-training 3D-visual-tactile dexterous policies on human and robot demonstrations. Glov...

J. Poffet, M. Strong, Ankush Dhawan et al. · 0 citations

#artificial intelligence Mar 2026

UniQueR: Unified Query-based Feedforward 3D Reconstruction

The UniQueR model learns a compact set of 3D anchor points that act as explicit geometric queries, enabling the network to infer scene structure, including geometry in occluded regions--in a single forward pass.

Chensheng Peng, Quentin Herau, Jiezhi Yang et al. · arXiv.org · 3 citations