Is your feature request related to a problem? Please describe.
Inspired by this paper:
P. Wieschollek, F. Groh, and H. P. A. Lensch. “Backpropagation Training for Fisher Vectors
within Neural Networks”. In: CoRR abs/1702.02549 (2017). arXiv: 1702.02549. url:
http://arxiv.org/abs/1702.02549.
I thought this would be an interesting experiment: the GaussianMixtureModel used used for Fisher Vector can actually be used as a neural network layer and hence trained via Backprop, which might improve the model's performance significantly. The same could be done for KMeans for VLAD.
Describe the solution you'd like
Under pyvisim/neural_networks, we can try to add a FisherNet or something similar, that uses this trick. If you also have time. in the demo notebooks, you can add a notebook demonstrating how to train a neural net and benchmark it against e.g. the OxfordFlowerDataset.
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Add any other context or screenshots about the feature request here.
Is your feature request related to a problem? Please describe.
Inspired by this paper:
I thought this would be an interesting experiment: the
GaussianMixtureModel usedused for Fisher Vector can actually be used as a neural network layer and hence trained via Backprop, which might improve the model's performance significantly. The same could be done forKMeansfor VLAD.Describe the solution you'd like
Under
pyvisim/neural_networks, we can try to add aFisherNetor something similar, that uses this trick. If you also have time. in the demo notebooks, you can add a notebook demonstrating how to train a neural net and benchmark it against e.g. the OxfordFlowerDataset.Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Add any other context or screenshots about the feature request here.