  This paper introduces a new method for inter-frame coding based on two
complementary autoencoders: MOFNet and CodecNet. MOFNet aims at computing and
conveying the Optical Flow and a pixel-wise coding Mode selection. The optical
flow is used to perform a prediction of the frame to code. The coding mode
selection enables competition between direct copy of the prediction or
transmission through CodecNet. The proposed coding scheme is assessed under the
Challenge on Learned Image Compression 2020 (CLIC20) P-frame coding conditions,
where it is shown to perform on par with the state-of-the-art video codec
ITU/MPEG HEVC. Moreover, the possibility of copying the prediction enables to
learn the optical flow in an end-to-end fashion i.e. without relying on
pre-training and/or a dedicated loss term.
