Yasemin Bekiroglu

Compositional Motion Generation From Demonstration With Object-Centric Neural Fields

This work proposes a generative learning-from-demonstration framework that enables compositional modeling of robotic behavior by connecting perception and motion through shared object-level representations, and renders scenes from object-centric neural representations that integrate canonical neural fields with latent-conditioned deformations.