Micro-object pose estimation with sim-to-real transfer learning using small dataset

High-resolution scanning tunnelling microscopy is a state-of-the-art imaging technique at the nanometer scale. This work presents a novel deep learning approach for 3D pose estimation of micro/nano-objects, particularly useful in regimes of limited experimental data.