Lossy Image Compression with Compressive Autoencoders

The quickest way to start experimenting is to use this model trained on this smaller dataset. An arbitrary dataset can be constructed by downloading frames using the scripts provided here.

See wiki for more details, download links and further results.

Results

• cae_32x32x32_zero_pad_bin model
• roughly 5.8 millions of optimization steps
• randomly selected and downloaded 121,827 frames
• left: original, right: reconstructed

References

[1] Lossy Image Compression with Compressive Autoencoders, Theis et al.

[2] Variable Rate Image Compression with Recurrent Neural Networks, Toderici et al.