Felix Mohr

The proposed LePoKet (Learnable Parameter Optimization for Knowledge Transfer), a structural transfer framework that embeds knowledge inheritance directly into the forward computation, demonstrates that learnable structural transfer generalizes across recognition and motion perception tasks and provides a promising approach for efficient robotic vision.