Abstract: A method for searching for one or more neural network (NN) architectures is provided. The method determines a search space comprising a plurality of architectures including one or more blocks, wherein a block of the one or more blocks is formed by one or more NN layers. The determining is based on a measure including: an amount of matrix operations, and/or one of: i) an amount of layer input data and/or layer output data, and ii) an amount of vector operations. The method searches for the one or more NN architectures in the determined search space.

Abstract: The present disclosure relates to encoding and decoding of a picture or a plurality of pictures (e.g. video) using a neural network which is partially trained online. Accordingly, at an encoder one or more layers are selected which are to be trained. Then, the training of the neural network is performed in which parameters of the selected layers are updated. The parameters of the remaining layers are maintained and not updated. The updated parameters are provided within a bitstream. The picture(s) is/are also encoded. The decoder receives an indication of the updated parameters, updates only those parameters indicated, and applies the so obtained neural network.