DEEP VIDEO COMPRESSION FOR INTERFRAME CODING

Hsueh-Ming Hang

Abstract:

A typical learning-based video compression scheme
consists of motion coding and residual coding. In this paper,
our deep video compression features a motion predictor and
refinement networks for interframe coding. To save the bits
for transmitting motion information, our scheme performs
local motion prediction and sends only the differential motion
vectors to the decoder. In the residual coding, we couple the
residual decoder with the refine-net to reduce residual signal
bits. The experiments show that our work can produce a very
competitive coding performance compared to the other
learning-based predictive video codecs.