Concept for further training of a pre-trained version of a decoder fitting to a variational picture autoencoder

An apparatus for further training a pre-trained version of a decoder fitting to a variational picture autoencoder, the decoder comprising

• a hyperdecoder for deriving statistical entropy-coding parameters from a quantized hyperprior in a data stream,
• an entropy decoder for decoding quantized latents from the data stream using the statistical entropy-coding parameters, and
• a latents-to-picture decoder for deriving from the quantized latents a decoded picture, the apparatus configured to
• provide a further training set of further training data elements corresponding to a further set of various test pictures, each further training data element comprising
• unquantized latents and quantized latents resulting from applying the variational picture autoencoder to an associated test picture, and
• train a hypercoder system comprising the hyperdecoder and a hyperencoder of the variational picture autoencoder on the further training set with respect to rate-distortion optimization to acquire a further trained version of the hyperdecoder and a further trained version of the hyperencoder.

A decoder fitting to a variational picture autoencoder, the decoder comprising

• a hyperdecoder for deriving statistical entropy-coding parameters from a quantized hyperprior in a data stream,
• an entropy decoder for decoding quantized latents from the data stream using the statistical entropy-coding parameters, and
• a latents-to-picture decoder for deriving from the quantized latents a decoded picture,
• wherein a parametrization of the latents-to-picture decoder lies in a minimum of a distortion function from a quantized latent domain to distortion with respect to parameters of the latents-to-picture decoder.

A system of a variational picture autoencoder and a decoder fitting to the variational picture autoencoder, wherein

• the decoder comprises
• a hyperdecoder for deriving statistical entropy-coding parameters from a quantized hyperprior in a data stream,
• an entropy decoder for decoding quantized latents from the data stream using the statistical entropy-coding parameters, and
• a latents-to-picture decoder for deriving from the quantized latents a decoded picture, and
• the variational picture autoencoder comprises
• the picture-to-latents encoder for deriving from a picture to be encoded unquantized latents,
• the latent quantizer for quantizing the unquantized latents to acquire the quantized latents,
• a hyperencoder for deriving a representation of the statistical entropy-coding parameters from the unquantized latents,
• a hyper quantizer for quantizing the representation of the statistical entropy-coding parameters to acquire the quantized hyperprior from which the statistical entropy-coding parameters are derivable by the hyperdecoder,
• an entropy encoder for encoding the quantized latents into the data stream using the statistical entropy-coding parameters,
• wherein a parametrization of the latents-to-picture decoder lies in a minimum of a distortion function from a quantized latent domain to distortion with respect to parameters of the latents-to-picture decoder
• and/or
• wherein a parametrization of a hypercoder system comprising the hyperdecoder and the hyperencoder lies in a minimum of a rate-distortion Lagrangian function from an unquantized-latents-and-quantized-latents domain to a Lagrangian sum of rate and distortion with respect to parameters of the hyperdecoder and the hyperencoder and fixedly with respect to the parametrization of the latents-to-picture decoder.