Method and data processing system for lossy image or video encoding, transmission and decoding

A method for lossy video encoding, transmission and decoding, the method comprising the steps of:

• receiving a plurality of frames of a video at a first computer system;
• encoding the plurality of frames using a first trained neural network to produce a plurality of latent representations;
• concatenating at least two of the plurality of latent representations to obtain a latent representation subset;
• encoding the latent representation subset using a second trained neural network to produce a hyper-latent representation;
• performing a quantization process on the latent representation to produce a quantized latent and the hyper-latent representation to produce a quantized hyper-latent;
• transmitting the quantized latent and the quantized hyper-latent to a second computer system;
• decoding the quantized hyper-latent using a third trained neural network;
• and decoding the quantized latent using the output of the third trained neural network and a fourth trained neural network to produce a plurality of output frames, wherein the plurality of output frames are an approximation of the plurality of frames of the video.

A method for lossy video encoding, transmission and decoding, the method comprising the steps of:

• receiving a plurality of frames of a video at a first computer system;
• concatenating at least two frames of the plurality of frames to obtain a video subset;
• encoding the video subset using a first trained neural network to produce a latent representation;
• performing a quantization process on the latent representation to produce a quantized latent;
• transmitting the quantized latent to a second computer system;
• and
• decoding the quantized latent using a second trained neural network to produce an output video subset, wherein the output video subset is an approximation of the video subset.

A method for lossy video encoding and transmission, the method comprising the steps of:

• receiving a plurality of frames of a video at a first computer system;
• encoding the plurality of frames using a first trained neural network to produce a plurality of latent representations;
• concatenating at least two of the plurality of latent representations to obtain a latent representation subset;
• encoding the latent representation subset using a second trained neural network to produce a hyper-latent representation;
• performing a quantization process on the latent representation to produce a quantized latent and the hyper-latent representation to produce a quantized hyper-latent;
• transmitting the quantized latent and the quantized hyper-latent.