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.

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.

Abstract: Systems and methods for displaying a three-dimensional video at a different frame rate from which the video was stored or acquired are described. In one aspect, a frame N corresponding to a frame number N in the video is received at a video reader and decoder. A 3D mesh including a plurality of vertices, a texture, and one or more offset vectors associated with each vertex of the 3D mesh in the frame N are retrieved and transmitted to a rendering device. At least one vertex of the 3D mesh is adjusted according to the corresponding offset vectors and a playback time moment. The playback time moment is between N and N+1, where N+1 is a frame number corresponding to a frame N+1 immediately following the frame N. The adjusted 3D mesh and the texture are rendered according to one or more camera parameters associated with a display device.

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.