Leonhard Sommer

Fine-grained 3D object understanding can emerge without explicit correspondence supervision by learning a shared morphable object prior, opening new avenues for robotic and AR/VR applications.

A dataset of 21.8 million images reveals that real-world 9D pose estimation can be scaled dramatically with minimal manual effort, setting a new benchmark for the field.