1 code implementation • CVPR 2020 • Daniel Haase, Manuel Amthor
Ultimately, we reveal that DSC-based architectures such as MobileNets implicitly rely on cross-kernel correlations, while our BSConv formulation is based on intra-kernel correlations and thus allows for a more efficient separation of regular convolutions.
Ranked #18 on Fine-Grained Image Classification on Stanford Dogs
no code implementations • CVPR 2014 • Daniel Haase, Erik Rodner, Joachim Denzler
Therefore, we present a transfer learning method that is able to learn from related training data using an instance-weighted transfer technique.