I'm not sure where it would help. The encoding process is slow so it wouldn't make sense to encode anything that changes like the inputs or activations, or the weights during training. You could maybe encode the weights after training but you'd really have to massage the data to fit into these formats, and the lossy perceptual tricks used here are designed for the human visual system, not high-dimensional convolution filters.