Can deep learning be applied to video compression?
[EDIT: addition of a March 2017 preprint] 

Deep learning already has many applications in video, like enhancement (Deep Convolutional Neural Network for Decompressed Video Enhancement) or semantic analysis.

Recently, there have been some announcements related to video compression, for instance:


Generative Compression (Preprint, March 2017)



  Traditional image and video compression algorithms rely on
  hand-crafted encoder/decoder pairs (codecs) that lack adaptability and
  are agnostic to the data being compressed. Here we describe the
  concept of generative compression, the compression of data using
  generative models, and show its potential to produce more accurate and
  visually pleasing reconstructions at much deeper compression levels
  for both image and video data. We also demonstrate that generative
  compression is orders-of-magnitude more resilient to bit error rates
  (e.g. from noisy wireless channels) than traditional variable-length
  entropy coding schemes.



Video: Deep Learning reconstructing Blade Runner for new video compression techniques
Wyner-Ziv Video Coding using Hadamard Transform and Deep Learning


How important is deep learning here, and what performances are obtained is not clear to me yet.