GitHub - wohlert/generative-query-network-pytorch: Generative Query Network (GQN...
source link: https://github.com/wohlert/generative-query-network-pytorch
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README.md
Generative Query Network
This is a PyTorch implementation of the Generative Query Network (GQN) described in the DeepMind paper "Neural scene representation and rendering" by Eslami et al. For an introduction to the model and problem described in the paper look at the article by DeepMind.
The current implementation generalises to any of the datasets described in the paper. However, currently, only the Shepard-Metzler dataset has been implemented. To use this dataset you must download the tf-records from DeepMind and convert them to PyTorch tensors.
Implementation
The implementation shown in this repository consists of the tower
representation architecture along with the generative model that is
similar to the one described in "Towards conceptual compression" by
Gregor et al.
Additionally, this repository also contains implementations of the DRAW model and the ConvolutionalDRAW model both described by Gregor et al. These serve as the basis for the generative model in the GQN.
Results
Currently, the results are pending as the model is very computationally costly to train for the datasets described in the paper.
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